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King, Mark, Legge, Matthew, Oviedo Trespalacios, Oscar, Regan, Michael,& Rakotonirainy, Andry(2017)Scoping study of mobile phone use while driving: Final Report.

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SCOPING STUDY OF MOBILE PHONE USE

WHILE DRIVING

Final Report

June, 2017

Mark King Matthew Legge

Oscar Oviedo-Trespalacios Michael Regan

Andry Rakotonirainy

The Centre for Accident Research & Road Safety – Queensland

is a joint venture initiative of the Motor Accident Insurance

Commission and Queensland University of Technology

MOBILE PHONE AND DRIVER DISTRACTION

FINAL REPORT i

TABLE OF CONTENTS

EXECUTIVE SUMMARY ................................................................................................................. V

1 INTRODUCTION ..................................................................................................................... 1

2 METHODS ................................................................................................................................. 2

2.1 Review of crash data ............................................................................................................................ 2

2.2 Literature review ................................................................................................................................. 2

2.3 Stakeholder consultations .................................................................................................................... 3

3 REVIEW OF AVAILABLE DATA .......................................................................................... 4

3.1 BACKGROUND ................................................................................................................................... 4

3.2 POLICE AND SELF-REPORTED DATA FROM JURISDICTIONS ....................................................................... 5

3.3 NATIONAL CORONIAL INFORMATION SYSTEM (NCIS) ........................................................................... 9

4 REVIEW OF CURRENT RESEARCH ON RISK OF MOBILE PHONE/DEVICE USE 10

4.1 Background and scope ........................................................................................................................10

4.2 Prevalence of mobile phone use while driving ....................................................................................11

4.3 General factors that influence mobile phone use while driving ..........................................................14

4.4 Relationship between mobile phone use and driving performance ....................................................16

4.5 Relationship between mobile phone use while driving and crash risk ................................................20

4.6 Mobile phone use while driving and regulatory approaches ...............................................................24

5 REVIEW OF CURRENT REGULATORY AND ENFORCEMENT PRACTICES ........... 28

5.1 Background .........................................................................................................................................28

5.2 Australian Road Rules Regulation 300 .................................................................................................28

5.3 Jurisdiction regulatory requirements ..................................................................................................30

5.4 Enforcement practices ........................................................................................................................33


FINAL REPORT ii

5.5 Common policy goals across jurisdictions ...........................................................................................37

6 SCOPE FOR EXISTING AND NEW TECHNOLOGICAL APPROACHES ..................... 40

6.1 Existing technological approaches to reducing the risk of mobile phone use ......................................40

6.2 New and potentially emerging technologies that have promise ..........................................................42

6.3 Evolving technologies that can contribute to driver distraction ..........................................................43

6.4 Recommended technological approaches ...........................................................................................44

7 NOMADIC DEVICES AND IN-CAR SYSTEMS ................................................................. 46

7.1 Apple CarPlay and Android Auto .........................................................................................................46

7.2 Integrated hands-free mobile phone conversations ............................................................................47

7.3 Text messaging using IVS ....................................................................................................................48

8 DISCUSSION ........................................................................................................................... 49

9 REFERENCES ......................................................................................................................... 51

APPENDIX A INTERVIEW SCHEDULE .................................................................................... 72

APPENDIX B SUMMARY OF DRIVER DISTRACTION LAWS ACROSS DIFFERENT

JURISDICTIONS (ADAPTED FROM WHO REPORT, 2011) ............................................... 73


FINAL REPORT iii

INDEX OF TABLES

Table 3.1 Fatalities by characteristic, Queensland, 2015 compared with 2014 and the 2010 to 2014 average5

Table 3.2 Persons seriously injured by factors/components of individual road trauma, Victoria, 2013/14

compared with 2014/15 ....................................................................................................................... 5

Table 3.3 Infringements or expiations issued for improper mobile phone use, 2011/12 to 2016/17 ............. 8

Table 4.1 Self-reported mobile phone use by jurisdiction, 2013 Community Attitudes Surveya ...................12

Table 4.2 Crash risk associated with mobile phone use ................................................................................22

Table 4.3 Crash risk associated with mobile phone use ................................................................................22

Table 5.1 Legislation and penalties for mobile phone use while driving .......................................................31

Table 5.2 Enforcement practices for mobile phone use while driving ...........................................................34


FINAL REPORT iv

INDEX OF FIGURES

Figure 3.1 Crashes by severity in New South Wales where handheld phone use was a contributing factor,

1997 to 2011 ........................................................................................................................................ 6

Figure 3.2 Number of fatalities and persons hospitalised in Queensland where handheld mobile phone use

was a contributing factor in the crash, 2010 to 2016 ............................................................................ 7

Figure 7.1 Cars have become highly complex with many interconnected systems .......................................46


FINAL REPORT v

EXECUTIVE SUMMARY

Background

The use of mobile phones and other mobile technologies has been increasing, and the effects

on driver distraction are of concern. Australian jurisdictions regulate mobile phone use while

driving and conduct enforcement, however there is a need to review current arrangements and

consider the possibilities for change in the context of a rapidly changing technological

environment. CARRS-Q was commissioned by The Department of Infrastructure and Regional

Development to undertake this scoping study, examining: crash data; research evidence;

regulatory and enforcement practices; technological solutions; and the implications of nomadic

devices interacting with in-car systems.

Methodology

Crash data were sourced from publicly available sources and requested via agency

channels. The National Coronial Information System (NCIS) was also investigated, as was

police infringement notice data. The academic and grey research literature were reviewed for

information on the crash risk associated with mobile phone use, and for evaluation of regulatory

and enforcement approaches. Transport and police agency officers were interviewed to develop

a picture of the regulatory frameworks and enforcement practices used in Australia, and to

discern common areas of policy interest. Information on possible technological solutions to

mobile phone distraction, and emerging technological challenges, were also reviewed and

discussed.

Results

The available crash data show very low involvement of mobile phone use in crashes, due to the

difficulty in determining whether a phone was being used at the time of the crash. Data from

naturalistic studies suggests that distracted driving is very common, and is associated with

increased crash risk, for example all forms of hand-held phone use combined were found to

increase crash risk by 3.6 times in one major U.S. study. While there is a methodological debate

about the validity of this figure and the risk of conversing on a mobile phone, there is agreement

that non-conversation use is associated with increased crash risk. Given the high rates of illegal

mobile phone use while driving, with 45% of respondents in a recent Australian study

locating/answering a phone on a typical day, the risk ratio found in the U.S. study implies that

contribution of mobile phone distraction to crashes in Australia is likely to be high. Police

impressions from the jurisdictions are that use is rising and becoming harder to detect,

consistent with the information from the literature.

Mobile phone use is regulated by Australian Road Rule (ARR) 300, which has been adopted as

is, or with minor variations, by each jurisdiction. Most jurisdictions apply additional

restrictions for P1 and P2 drivers, and there are other variations in offences. The size of the

financial penalties varies between $250 and $511 between jurisdictions, the number of demerit


FINAL REPORT vi

points varies between 3 and 4, and the application of double demerit points applies in some

jurisdictions for either holiday periods or multiple offences within a year. While the core of the

regulatory frameworks is ARR 300, there is variation across jurisdictions that could be

addressed.

Enforcement data generally show little increase in enforcement, most likely a decrease

compared with population growth, even though there is a strong impression that distracted

driving has increased. Police report most commonly using motorcycles to detect mobile phone

use among drivers, and to a lesser extent cameras, and there is variation between jurisdictions

in the evidentiary provisions that apply to the use of cameras. A new camera system is being

trialled and could be promising if it is possible to develop an image processing algorithm that

will detect mobile phone use. Several jurisdictions commented that enforcement alone was

unlikely to be effective, and proposed a need for technological solutions and for social change

to enable people to manage their use of mobile phones in a safer way. The research literature

does not provide much information about effective enforcement and penalties for guidance.

New technologies such as in-vehicle workload managers and workload management apps are

being developed, but there is almost no evaluation of their acceptance and effectiveness. At the

same time, new and potentially distracting technologies are also emerging. A similar situation

applies with nomadic technologies, where better integration of systems through applications

such as Apple CarPlay and Android Auto can enable voice activated mobile use, but at the same

time may still require some manual operation and draw the driver’s attention away from the

road. While voluntary lock-out systems are already available as apps or proprietary software

(e.g. Apple’s ‘Do Not Disturb’ feature), they are unlikely to be used by drivers who constitute

the greatest risk due to their prioritisation of staying connected. An EU report on good practice

(in the absence of evaluation data on best practice) rated lock-out systems and workload

managers as the least effective anti-distraction measures, instead favouring anti-collision

warning devices that do not prevent distraction, instead warning distracted drivers of danger. It

appears that the lack of maturity of lock-out technology has contributed to low acceptance, so

that it may have potential in the future.

Limitations

Constraints on the time available for this review limited the amount and range of crash and

enforcement data that could be collected, although the participation of agency representatives

was almost universal.

Future Directions

A key focus of this study was to recommend ways that Australian jurisdictions could address

mobile phone distraction more effectively. It was noted that the structure of government in

Australia entails the need for consensus among the jurisdictions, and that the approach taken to

road safety across Australia relies on an evidence-based approach. Consideration of these


FINAL REPORT vii

points suggests that, in the short/medium term, the best way to work towards a nationally agreed

policy direction is to:

Consult researchers with relevant expertise to determine the evidence base on which

policy can be developed, including a resolution of the current active debate on the

validity of naturalistic driving study crash risk estimates, i.e. whether the data indicate

that hands-free conversation constitutes a crash risk

Investigate means of collecting valid, reliable and comprehensive data on mobile phone

involvement in road crashes, such as in-vehicle recording of phone use immediately

before a crash

Explore enforcement options that can be implemented by all jurisdictions, including the

possibility of automated enforcement based on technology currently being trialled in

Western Australia

Explore technology options that balance the costs and benefits of reducing or blocking

connectivity of mobile phones in vehicles; at present there is evidence that these

technologies are not sufficiently developed and as a result have low user acceptance

In the longer term, the social context of mobile phone use needs to be explored and addressed,

though this would take place in a broader context and draw on social education approaches.

Schools around Australia already address both negative and positive aspects of mobile phone

use, however the notion of “mobile phone addiction” is an emerging issue that appears not to

be systematically addressed as yet.


FINAL REPORT 1

1 INTRODUCTION

The wide uptake of mobile phone and other mobile technologies has raised concerns about the

prevalence and impact of driver distraction, and how to address the problem through regulation

and enforcement. The Department of Infrastructure and Regional Development has

commissioned the Centre for Accident Research and Road Safety - Queensland (CARRS-Q) at

the Queensland University of Technology (QUT) in collaboration with the Australian Road

Research Board (ARRB) to undertake a scoping study encompassing the following tasks:

Review of available data on the contribution of mobile phone/device distraction to fatal

and serious injury crashes in Australian jurisdictions.

Review of current available Australian and international research evidence and

regulatory approaches in relation to the risk of mobile phone use and device use -

including calling, texting and social media use - while driving.

Review of the current regulatory regimes and enforcement practices across Australia

and the identification of common policy goals across jurisdictions.

Consideration of the scope for existing and new technological approaches to assist in

reducing the risk of mobile phone use.

Consider how nomadic devices are used in relation to in-car systems and the interaction

of these devices with other in-car technology.

This report outlines the methodology used to undertake the review, which covers the solicitation

of crash and infringement data, a review of the literature on crash risk related to mobile phone

use, consultation with transport and police agencies on the regulatory framework and

enforcement approaches, and identification of technology challenges and possible

solutions. Recommendations are made regarding future development of policies and

regulations.


FINAL REPORT 2

2 METHODS

2.1 REVIEW OF CRASH DATA

Publicly available crash data sources from each Australian State and Territory were examined

for information on the contribution of distraction from any sources and mobile phones/devices

in particular. These sources include annual reports published by Police services and Transport

authorities, interactive self-service web pages where data can be downloaded in tabular and

graphical form and de-identified unit records via open data portals. Requests for annual counts

of the number of fatalities and seriously injured crash casualties where distraction and mobile

phone use were contributing factors, were also made to the crash data custodians in each

jurisdiction.

These sources were also searched for information on the number of infringements issued for

improper use of mobile phones while driving. Specific requests for infringement data were also

made to the data custodians.

An additional source of information on the contribution of mobile phone use in fatal crashes is

the National Coronial Information System (NCIS). The NCIS contains information about

deaths reported by coroners in Australia and New Zealand. The data records demographic

information about the case, time, location and activity at the time of the incident and death,

cause of death and for external cause of death, the mechanism of injury and the object or

substance involved. Police narratives of the circumstance, pathology reports, toxicology reports

and coronial findings are also attached to the case record. A request was made to the NCIS to

count the number of motor vehicle fatalities who were injured in crashes involving a mobile

phone, and to conduct a review of the coronial findings and police reports attached to a subset

of these fatalities.

2.2 LITERATURE REVIEW

A comprehensive literature review of available practice and evaluation tools relating to the risk

of mobile phone use and device use, and regulatory approaches was conducted. For the purpose

of this review, we have investigated national and international literature on mobile phone use

while driving, with a focus on Australia and New Zealand. Relevant material from elsewhere

around the world is included, with emphasis on countries with similar road safety performance

(nearly 5.4 fatalities per 100,000 population (WHO, 2015)) or scientific significance such as

the U.K. and U.S.A. Particularly, we included literature when cultural and social differences

have not played a significant role in shaping the results. Peer-reviewed and grey literature has

been covered.

The review involved a systematic search of various sources (outlined below) including both

published and grey literature. Relevant research findings were identified by searching:


FINAL REPORT 3

- Transport, social science, health, and road safety online databases (e.g., Pub Med,

Science Direct, Ebsco, Proquest, Blackwell Synergy, TRIS online);

- Generic internet search engines (e.g., Google scholar);

- Websites of recognised road safety organisations;

- Published government reports;

- Peer-reviewed conference proceedings (e.g. Australasian Road Safety Conference;

Annual Meetings of the US Transportation Research Board; International

Conference on Traffic and Transport Psychology etc);

- Manual searches of key road safety journals (e.g., Accident Analysis and

Prevention); and,

- Cross-referencing of obtained studies.

2.3 STAKEHOLDER CONSULTATIONS

Stakeholder consultations were conducted in order to obtain information on the regulation and

enforcement approaches taken by different Australian jurisdictions. The discussions

encompassed regulatory approaches, their advantages and shortcomings. In addition, secondary

sources available on transport and police websites for each State were reviewed. Discussions

also canvassed the issue identified above regarding police reporting of mobile device use in

crashes, in terms of system disincentives to report, and alternative approaches and police data

sources (See Appendix A for interview guide).

Representatives from transport authorities and police in all Australian jurisdictions were invited

to take part in an interview via phone with a member of the research team. Consultations have

been held with representatives of transport authorities in all Australian jurisdictions. With

regards to the police, at the time of submission of this final report, consultations have been held

with representatives from all jurisdictions, with the exception of Victoria.


FINAL REPORT 4

3 REVIEW OF AVAILABLE DATA

3.1 BACKGROUND

Each Australian State Police agency is responsible for collecting information on road crashes,

and this data can be used to determine whether charges should be laid for individual crashes, to

monitor trends in road crashes both overall and by category (e.g. road user type, severity level,

crash type, crash location, offence involved), and to identify emerging problems so that they

can be addressed. Crash report forms are designed to meet these needs, although in practice

they often represent a compromise between the immediate needs of police and the research

needs. Crash forms incorporate items that identify factors that are considered to have

contributed to a crash, with the word “contributed” being preferred to “caused” for both legal

and scientific reasons. Many of the crash report items and contributing factors have been

standard for decades, however the widespread uptake of mobile phones and an increasing array

of other mobile technologies that can distract drivers has created an ongoing challenge for

police to identify and report on instances where distraction from such sources has contributed

to a crash.

The main aim of this part of the scoping study was to examine crash data from Australian police

agencies to ascertain how distraction by mobile phones and other mobile technologies is

recorded, and the reported prevalence of crashes to which this form of distraction has

contributed. At the outset, the expectation was that there would be low levels of reporting

because of the difficulties involved in determining whether technology was being used just

before or during the crash, and because drivers involved in crashes may not report forms of

distraction. The likely scale of distracted driving will be addressed in more detail in section 4,

where naturalistic driving studies have provided a previously unseen level of information about

what drivers are doing at the time of a crash.

A second approach to this task involved ascertaining the possibility of obtaining data from the

National Coronial Information System (NCIS). As a repository for detailed coronial

information from around Australia, NCIS has the potential to provide rich data about the

circumstances of fatal crashes, including qualitative judgements about the possible involvement

of distraction in the crash. However, obtaining ethical approval to access the NCIS records, the

expected timeline to have the request processed and financial requirements to access these

records could not be fulfilled within the time constraints of this study.

Finally, as part of the consultation with agencies outlined in section 5, contacts from police and

transport agencies were asked about the crash investigation process in each jurisdiction, i.e.

how the potential contributing factors are investigated, prioritised and reported on. As part of

this, we examined the possibility that legal and other considerations may provide a disincentive

for police to report possible mobile device use, based on informal information that this was an

issue in at least one jurisdiction.


FINAL REPORT 5

3.2 POLICE AND SELF-REPORTED DATA FROM JURISDICTIONS

3.2.1 PUBLICLY AVAILABLE CRASH DATA

Queensland (Department of Transport and Main Roads, 2016) and Victoria (VicRoads, 2016)

have published reports that include counts of the number of people killed and seriously injured

in crashes when distraction was a contributing factor in the crash. New South Wales has

published a series of reports, for example Centre for Road Safety (2016), that recorded the

number of crashes where distractions from sources inside or outside the vehicle were a factor

between 1997 and 2015. Between 1997 and 2011, this series also reported on the number of

crashes where the use of a hand-held mobile phone was a contributing factor.

In Queensland between 2010 and 2014, an average of 12 (5%) fatalities per year were the result

of a crash involving a distracted driver or rider. In 2015, this increased to 25 (10%). In Victoria,

over the 3 years from June 2010 to July 2014, an average of 216 (4%) people per year were

hospitalised from crashes involving distracted drivers or riders. In the 2014/15 financial year

there were 223 (5%) people hospitalised in distraction related crashes. Information on the

number of fatalities from crashes involving distracted or inattentive drivers or riders was not

available.

Table 3.1 Fatalities by characteristic, Queensland, 2015 compared with 2014 and the 2010 to 2014 average

Characteristic

2010 to 2014

average 2014 2015 2015 vs 2014

2015 vs 2010 to

2014 average

n % n % n % n % n %

Involving

distracted/inattentive

drivers/riders

12 4.7% 12 5.4% 25 10.3% 13 108.3% 12.8 104.9%

All fatalities 258 - 223 - 243 - 20 9.0% -15.4 -6.0%

Table 3.2 Persons seriously injured by factors/components of individual road trauma, Victoria, 2013/14

compared with 2014/15

Factor/Component 2014/15 2013/14

2013/14 to

2010/11 ( 3 year

average)

% change

2014/15 vs

2013/14

% change

2014/5 vs 3 year

average

n % n % n % n n

Distracted drivers and

riders 223 5% 267 5% 216 4% -16.5 3.2

Total persons

seriously injured 4951 - 5198 - 5266 - -4.8 -6.0

In New South Wales between 1997 and 2011 (Centre for Road Safety, 1999, 2000a, 2000b,

2001, 2003, 2004a, 2004b, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012) there was an

average of 1 (0.1%) fatal crash every two years associated with the use of a hand-held mobile

phone. In comparison there was an average of 3 (0.6%) fatal crashes per year associated with a

source of distraction inside a vehicle and 22 (5%) fatal crashes per year associated with a source


FINAL REPORT 6

of distraction outside the vehicle. The involvement of distraction and hand-held mobile phone

use had a similar pattern among all reported crashes in New South Wales over the same period.

In New South Wales for all reported crashes, an average of 34 (0.1%) crashes were associated

with hand-held mobile phone use, 988 (2.1%) crashes were associated with an inside vehicle

distraction and 3071 (6.4%) crashes per year were associated with a source of distraction

outside of the vehicle.

Figure 3.1 Crashes by severity in New South Wales where handheld phone use was a contributing factor,

1997 to 2011

3.2.2 REQUESTED CRASH DATA

Following the review of publicly available data sources, requests for tables counting the number

of fatalities and people seriously injured in crashes involving distraction or inattention and

mobile phone use in particular were sent to each data custodian in each jurisdiction.

As at writing, data on distraction and mobile phone use have been obtained from Queensland

(Department of Transport and Main Roads, 2017b) and Tasmania (Department of State Growth,

2017). Data from Western Australia (Main Roads Western Australia, 2017) and data extracts

from South Australia (Department of Planning Transport and Infrastructure, 2017) and the

Australian Capital Territory (Transport Canberra and City Services Directorate, 2017) have also

been provided, however, these datasets only record whether driver or rider inattention played a

role in the crash. The VicRoads Crash Information System does not record contributing factors

of crashes (Vic Roads, personal communication, 25 May 2017) and Victoria Police does not

corporately record the contribution of mobile phones in crashes (Victoria Police, personal

communication, 21 June 2017). The crash data from the Northern Territory does not record


FINAL REPORT 7

distraction or inattention as a contributing factor (Department of Infrastructure Planning and

Logistics, personal communication, 7 June 2017). CARRS-Q is still in communication with the

New South Wales Centre for Road Safety. The NSW crash data extracts have been authorised,

but have not yet been provided.

In Queensland between 2011 and 2015, there were 1 or 2 fatalities (0.5%) per year where

distraction due to mobile phone use was a contributing factor. In 2016, there were 5 (2%)

fatalities where mobile phone use was a contributing factor. From 2011 to 2016, between 9 and

21 (0.25%) people were hospitalised in crashes where mobile phone use was identified as a

contributing factor.

Figure 3.2 Number of fatalities and persons hospitalised in Queensland where handheld mobile phone use

was a contributing factor in the crash, 2010 to 2016

In Tasmania, a total of 3 (1.7%) road traffic fatalities between 2012 and 2016 were as a result

of crashes where distraction due to mobile phone use was a contributing factor. Over the same

five year period, 5 (0.5%) of the people hospitalised in traffic crashes were injured in crashes

where mobile phone use was a contributing factor.

The number of people killed and seriously injured in crashes Tasmania where mobile phone

use was identified as a contributing factor are too low to establish whether there is a trend.

However, in the Queensland there was statistically non-significant decreasing trend in the

number of people killed and seriously injured in crashes where a mobile phone was a

contributing factor.


FINAL REPORT 8

3.2.3 INFRINGEMENT AND EXPIATION DATA

An additional potential source of information regarding the prevalence of mobile phone use are

the number of infringements issued or expiations made for improper use of mobile phones while

driving. Table 3.3 provides a time series of the number of infringements or expiations from

2011/12 to 2015/16 financial years and for the 2016/17 year to date. From 2011/12 to 2015/16,

where full years of data are available, only Queensland appeared to have a statistically

significant trend in the total number of mobile phone infringements per year. In Queensland,

the figures suggest a decreasing trend in total infringement counts, with an average reduction

of 2293 infringements per year. However, caution must be used when interpreting this data, as

it is subject to the level of Police enforcement activities. They therefore, may not be a consistent

measure of the prevalence of improper use of mobile phones while driving.

Table 3.3 Infringements or expiations issued for improper mobile phone use, 2011/12 to 2016/17

Jurisdiction Infringement or expiation

issued

2011/12 2012/13 2013/14 2014/15 2015/16 Year to

date

2016/17*

New South Walesa Learner or provisional driver 806 682 726 750 982 1684

Open licence holders 41572 35923 33772 34620 37459 32587

Total 42378 36605 34498 35370 38441 34271

Queenslandb Learner driver 1 2 5 11 3 1

P1 provisional driver 19 27 27 40 32 36


Total 29961 27613 27320 24610 19995 12065

South Australiac Learner driver 11 14 11 14 8 5

P1 provisional driver 411 571 522 479 293 177


Total 9068 12579 12794 13312 11794 9142

Northern Territoryd Learner or provisional driver 14 5 2 15 10

Open licence holders 936 781 479 527 414

Total 950 786 481 542 424

Tasmaniae Using hand-held mobile

phone 3241 2141 2914 3256 3273 -

* Please note that data for the 2016/17 financial year is for a period of less than 12 months: New South Wales

to April 2017, Queensland to February 2017, South Australia to March 2017 and Northern Territory not stated.

a. NSW - Office of State Revenue (2017)

b. Queensland - Department of Transport and Main Roads (2017a)

c. South Australia - South Australia Police (2017a, 2017b, 2017c, 2017d, 2017e, 2017f)

d. Northern Territory - Department of Infrastructure Planning and Logistics (2017)

e. Tasmania - Department of Police and Emergency Management (2011, 2012, 2013, 2014, 2015); Department

of Police Fire and Emergency Management (2016)


FINAL REPORT 9

3.3 NATIONAL CORONIAL INFORMATION SYSTEM (NCIS)

A data query was sent to NCIS asking for tabular data on traffic and non-traffic fatalities where

the mechanism of death was 'Distraction by Personal Use Item' and the object involved was

'Mobile Phone'.

NCIS personnel conducted a search of the database for records meeting these criteria and

identified 36 motor vehicle incident cases, across all jurisdictions since July 2000 (National

Coronial Information System, 2017). The NCIS noted that mechanism and object of injury are

not consistently coded across jurisdictions, and suggested that the only way to identify relevant

cases would be to conduct a manual review of all land transport injury cases in their database.

To test the feasibility of this suggestion, the NCIS conducted a manual review of 111 motor

vehicle fatalities from January 2014. This review identified only one case where a mobile phone

was implicated in the crash. The review found that the attached coronial findings and police

narratives routinely mentioned a variety of contributing factors such as weather conditions,

drug/alcohol intoxication, excessive speed or mechanical fault. However, potential mobile

phone use was infrequently mentioned. There were a small number of fatalities where the police

narrative indicated that the deceased’s mobile phone had been examined to determine whether

the phone had been in use at the approximate time of the crash.

From this review, the NCIS indicated that since mobile phone use in incident cases was not

consistently coded in the database across jurisdictions and it was not frequently mentioned in

the attached documents, further review of cases is unlikely to elicit additional information

useful for this project (National Coronial Information System, personal communication, 30

May 2017).


FINAL REPORT 10

4 REVIEW OF CURRENT RESEARCH ON RISK OF MOBILE PHONE/DEVICE USE

4.1 BACKGROUND AND SCOPE

Although car use has been in decline in Australian car-dependent cities (e.g. Brisbane

metropolitan area (Li, Dodson, & Sipe, 2015), driving is still a common activity in the daily

lives of millions of Australians. Driving as a transport behaviour has critical social and

economic roles but also constitutes large risks for quality of life, including injury and death.

During the 12 months ending April 2017, there were 1,235 road deaths registered in Australia

(BITRE, 2017). Additionally, rates for people seriously injured in Australia due to a road

vehicle traffic crash increased an average of 0.9% over the 10-year period from 2001 to 2010

(Henley & Harrison, 2016). Notable improvements in technologies such as cooperative

intelligent transport systems and driving automation are expected to benefit road safety.

However, estimates suggest that population-wide benefits are only likely to be observed in the

long term (Dia, 2016) due to numerous challenges related to infrastructure investment (Clark,

Parkhurst, & Ricci, 2016), public perception (Kyriakidis, Happee, & de Winter, 2015), and

vehicle design policies (Smith, 2016). Until active safety technologies are completely

accessible to all drivers, it will be necessary to understand current road safety issues to prevent

road trauma.

Inadequate interactions between drivers and vehicles play a significant role on vehicle

collisions, which may result in injury or fatalities (Petridou & Moustaki, 2000). Drivers alter

their driving performance due to a wide range of factors, including fatigue, mobile phone use,

mood, etc. Mobile phone distracted driving is recognised as one of the most important human

factor issues in road safety worldwide (WHO, 2011). Conservative estimates suggest that

distracted drivers are heavily overrepresented in road traffic crashes. In the US, mobile phone

distraction is reported to contribute to about ten percent of road traffic crashes (NHTSA, 2017).

The recent naturalistic study in the US, Second Strategic Highway Research Program

Naturalistic Driving Study (SHRP 2 NDS), has reported that hand-held mobile phone

interactions increase the odds of crash risk as much as 3.6 times (Dingus et al., 2016). A survey

of 3706 drivers conducted in Australia reported that almost one in two Australian drivers aged

between 18 and 24 years use a hand-held mobile phone while driving, nearly 60% of them send

text messages, and about 20% of them read emails and use their phone for navigation (AAMI,

2012). Mobile phone distracted driving is likely to increase in future given the pervasiveness

of this ubiquitous technology (Brace, Young, & Regan, 2007).

Most of the research on mobile phone distracted driving in the last 10 years has been concerned

with tasks such as conversations and texting/browsing (Oviedo-Trespalacios, Haque, King, &

Washington, 2016). Mobile phones today provide a wide range of functions, such as taking

pictures, writing notes, making voice recordings, filming short videos, listening to music,

among many others that can be performed while driving. Indeed, studies have found that drivers

record themselves speaking to a camera (Hawkins & Filtness, 2015), playing games such as


FINAL REPORT 11

Pokemon Go (Ayers et al., 2016), interacting with social media (Gauld, Lewis, White, &

Watson, 2016), and playing/changing music while they were driving (Steinberger, Moeller, &

Schroeter, 2016). Mobile phones are emerging technologies with frequent changes in software

and hardware. The ongoing evolution requires the application of user-centred approaches to

measure the impact of mobile phones on driving performance and crash risk. Therefore, in this

review, when possible, behaviours were studied based on the type of interaction involved. For

example, texting or internet usage involves visual, cognitive and physical demand, compared

to listening to music which involves only cognitive demand, and hands free voice calls involve

auditory and cognitive demand.

Different mobile phone tasks have distinct impacts on drivers. These generally depend on the

type of interaction and user requirements, e.g. mobile phone conversations are usually

associated with an increased cognitive workload (Oviedo-Trespalacios, Haque, King, &

Washington, 2016), while texting and browsing on a mobile phone are usually associated with

physical, visual and cognitive demands that may impair smoothness or proficiency in driving

motion (Choi et al., 2013). Consequently, the risk of crash varies depending on the type of task

performed by the driver, e.g. talking on a hand-held mobile phone increased crash risk by about

2.2 times while texting while driving was found to increase crash risk by about 6.1 times

(Dingus, et al., 2016). There is, however, some dissenting evidence that argues that under

certain circumstances (e.g. no traffic) some mobile phone tasks such as conversing do not

increase crash risk (Young, 2017). Additionally, some studies have identified that in certain

environmental conditions, mobile phone distraction might serve as a protective factor against

collisions. Fitch, Hanowski, and Guo (2015) reported that hands-free conversations were

associated with a reduced risk of crashes along merging ramps or near intersections. This

phenomenon has been proposed as a result of self-regulatory strategies (also known as risk

compensation behaviours) that drivers perform to manage the secondary task (Young, 2015).

4.2 PREVALENCE OF MOBILE PHONE USE WHILE DRIVING

Prevalence of mobile phone use while driving has been examined in terms of texting, having a

conversation while holding the phone, and using the internet. Traditionally, self-reported

measures have been used for assessing prevalence of mobile phone use while driving. The self-

report methods have inherent limitations such as influence of social desirability or faulty

memories. However, recent research suggests that self-report data could be consistent with

actual police records in Australia (Ivers et al., 2009) and objective observed driving behaviour

in driving simulators (Zhao et al., 2012). Objective measures have been applied to study the

prevalence of mobile phone use while driving in observational and naturalistic designs.

Observational studies involve the observation of drivers at selected intersections or midblock

segments, whilst naturalistic studies involve the continuous observations of a group of drivers.

Literature in these areas is reviewed next.


FINAL REPORT 12

4.2.1 SELF-REPORTED ESTIMATES OF MOBILE PHONE USE WHILE DRIVING

The most comprehensive recent breakdown of self-reported mobile phone use while driving

across Australian jurisdictions can be found in the report on the results of the 2013 Community

Attitudes to Road Safety survey (Petroulias, 2014). The relevant table appears below (Table

4.1)

Table 4.1 Self-reported mobile phone use by jurisdiction, 2013 Community Attitudes Surveya

Have

mobile

phone

Answer calls

when driving

Make calls

when driving

Read text

when

driving

Send text

when

driving

Use mobile

phones when

drivingb

NSW 88 40* 34 26 17 47*

VIC 90 54 29 27 11* 60

QLD 91 55 27* 32 20 62

SA 88 44* 23* 21* 16 50*

WA 93 54 35 27 15 59

TAS 90 39* 20* 22* 7* 46*

NT 89 55 22* 21* 6* 57

ACT 96* 62 34 28 16 64

* Statistically significant at the 0.05 level

a. Petroulias (2014), excerpt from Table 6.2b, p. 68, based on 1058 landline phone interviews with active drivers

b. Have ever made or received calls or text messages

These figures indicate high levels of phone ownership and use; it is not possible to assess the

difference between hand-free (legal for most drivers) and hand-held (illegal) use for calls, but

reading and sending text (which are both illegal) were reported by about quarter and an eighth

of respondents respectively. It can be seen that the patterns vary between jurisdictions, with

Tasmania, the Northern Territory and South Australia being at the low end in most categories.

The most recent study available was conducted in South-East Queensland during 2016 by

Oviedo-Trespalacios, Haque, King, and Washington (under review). A total of 484 drivers

completed an on-line questionnaire studying four mobile phone-related behaviours where they:

(i) Located and answered a ringing phone, (ii) Spoke on a hand-held phone, (iii) Texted or

browsed on their phone, (iv) Looked at a hand-held phone while driving for more than 2

seconds. Of these respondents, 34.9% were males. With respect to age group, 49.8% were aged

17-25 years and 50.2% were aged 26-65 years. The average time with a valid licence was 3.33

years (SD = 0.13) for the 17-25 years old group, and 18.25 (SD = 0.72) for the 26-65 years old

group. On the one hand, on a typical day, 45% of participants reported that they

located/answered a ringing phone, and 28% spoke on a hand-held phone. To the extent that the

data are comparable, these figures are consistent with Table 4.1, although this study looked at

use in a “typical day” and estimated the amount of use per day. Drivers who located and

answered a ringing phone did this task on an average 1.5 times per hour of driving, and the


FINAL REPORT 13

average length of conversations among those who spoke on a hand-held phone was 9 minutes.

On the other hand, on a typical day, 34% of participants reported that they texted or browsed

and 39% looked continuously at their phone for more than 2 seconds. For every hour driving,

participants reported engaging 3.5 times in texting and browsing and 3.9 times looking at their

phone continuously for more than 2 seconds. In general, the most frequent interactions reported

by drivers in Queensland involve heavy visual workload. While typical behaviours such as

texting and calling were low, similar tasks in terms of interactions (i.e. located and answered a

ringing phone, and looked at a hand-held phone while driving for more than 2 seconds) were

highly prevalent.

Previous studies in Australia have confirmed a high prevalence of mobile phone use while

driving. A New South Wales (NSW) study found, from a sample of 181 mature drivers (M =

36 years; SD = 12.8; 21% males), that 44% of drivers answered calls, 29% had hand-held

conversations, 57% browsed in the phone, and 28% texted during the past week (Waddell &

Wiener, 2014). These figures are similar to those in Table 4.1, with the exception of browsing,

which was not asked about in the community attitude survey but was reported at high rates here.

A study in Western Australia (WA) and NSW (McEvoy, Stevenson, & Woodward, 2006), using

a sample of 1347 licensed drivers aged 18-65 years, showed that in the last trip (of 5 minutes

or more duration), 9% reported mobile phone use, a figure not directly comparable to those

above because a different counting base was used. In Victoria, a study of 295 drivers aged 18-

83 years found that 35% of drivers engaged in hand-held conversations, 64.3% read text

messages, and 55.4% sent text messages while driving (Young & Lenné, 2010), showing much

higher rates of texting than presented in Table 4.1 for Victoria. A Queensland (QLD) study

found that 33.4% of drivers answered a hand-held phone, 27.4% of drivers initiated a call on a

hand-held phone, 26.3% of drivers read a text, and 18.9% of drivers sent a text at least once a

day (White, Hyde, Walsh, & Watson, 2010). Compared with Table 4.1, this indicated much

higher levels of texting and a lower amount of answering voice calls, although the question was

asked about hand-held phones

The lack of comparability between these results points to a need to define the behavioural

measures of interest, and the time frames and frequencies of usage that are relevant, in order to

obtain data to allow comparison between jurisdictions and over time.

A large body of international research has investigated the prevalence of mobile phone use

while driving. Regarding texting, 46.56% (n = 6168) of U.S. drivers (18-44 years) texted while

driving in the previous 30 days (Qiao & Bell, 2016), 73.30% and 57.30% (n = 4964) of U.K.

drivers read and sent text messages, respectively, (Benson, McLaughlin, & Giles, 2015), and

66.2% and 52.3% (n = 962) of New Zealand participants (16-80 years) reported reading and

sending, respectively, at least 1–5 text messages while driving during a typical week (Hallett,

Lambert, & Regan, 2012). Regarding talking on a mobile phone, 91% (n = 4964) of U.S. drivers

(M = 21.8) phoned while driving at least some of the time (Hill, Styer, Fram, Merchant, &

Eastman, 2015), and 60.4% (n = 962) of participants (16-80 years) reported conversing on their


FINAL REPORT 14

cell phone while driving per week in New Zealand (Hallett, Lambert, & Regan, 2011). All these

figures are comparable with the high end data found in the Australian research above.

4.2.2 OBSERVATIONAL AND NATURALISTIC ESTIMATES

The most recent observational study available was conducted at 61 sites in metropolitan

Adelaide and rural regions within SA in 2009 by Wundersitz (2014a). Of the 11,524

observations registered, nearly 0.6% identified using hand-held phones. Earlier observational

studies in Melbourne have shown hand-held mobile phone use prevalence of 2% (n = 17023)

at 12 highway sites in 2002 (Taylor, Bennett, Carter, Garewal, & Barnstone, 2003), and 1.6%

(n = 20207) at 12 highway sites in 2006 (Taylor, MacBean, Das, & Rosli, 2007). More recently

in Melbourne, an observational study conducted by Young, Rudin-Brown, and Lenné (2010)

revealed that 1.4% (n = 5813) of drivers were talking on a hand-held mobile phone, 1.5% of

drivers were texting, 1.4% of drivers were talking by speaker or headset, and 0.2% of drivers

were dialling/answering a mobile phone at three heavy-traffic intersection sites in 2009. No

data for other states or territories in Australia was available.

Observational studies conducted in the U.S. found among 3265 drivers observed at

intersections, a prevalence of 31.4% of drivers were talking and 16.6% texting or dialling on

the phone (Huisingh, Griffin, & McGwin Jr, 2015). Other observational studies around the

world have estimated that 3.4% of a total of 7168 drivers use mobile phones for hand-held

interactions and hands-free conversations while driving in the U.K. (Sullman, Prat, & Tasci,

2014), 1.7% of a total of 6578 drivers in Spain use mobile phones for talking and texting (Prat,

Planes, Gras, & Sullman, 2015), and 1.34% of a total of 9520 drivers in moving cars in New

Zealand (Wilson, Thomson, Starkey, & Charlton, 2013).

In the U.S., the Second Strategic Highway Research Program Naturalistic Driving Study (SHRP

2 NDS) mobile confirmed phone use is reported to interfere with the driving task almost one

fifth of the driving time (Dingus, et al., 2016).

4.3 GENERAL FACTORS THAT INFLUENCE MOBILE PHONE USE WHILE DRIVING

Some groups of the population seem more susceptible to mobile phone distraction than others.

Alarmingly, distracted driving, particularly the use of mobile phones while driving, is more

prevalent among young drivers aged 18-24 years, a group that already had a higher crash risk

before the advent of mobile phones. In Australia, Young et al. (2010) confirmed through an

observational study that young drivers (<30 years) more frequently use hand-held mobiles than

middle-aged and older drivers (30 years and more) while driving. This is in accordance with

international studies, where at least one in two young drivers in U.S. and Canada have been

found to use a mobile phone while driving (Tucker, Pek, Morrish, & Ruf, 2015). There may be

gender differences within distracted drivers: recently in Victoria, males were observed to have

a larger engagement in mobile phone distracted activities than females (Wundersitz, 2014b).


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A recent study in Queensland determined predictors of mobile phone use for talking and

texting/browsing on a typical day (Oviedo-Trespalacios, et al., Under Review). Drivers who

have held a valid driving licence for less time and spend more time driving per day were more

likely to report mobile phone use for talking and texting while driving. Additionally, having at

least one traffic offence in the last three years was a predictor of actual self-reported usage of

mobile phone while driving. Recidivism might play a role and brings new opportunities for

developing targeted interventions for this high-risk group by imposing participation in an

intervention program as part of the penalties. Attitudes and beliefs were predictors of mobile

phone engagement on a typical day for talking and texting. Previous research has confirmed the

role of attitudes and safety beliefs in the prediction of mobile phone distracted driving behaviour

(Gauld, et al., 2016b; Walsh, White, Hyde, & Watson, 2008; Zhou, Yu, & Wang, 2016).

Engagement in task-management strategies was a predictor of mobile phone involvement on a

typical day for talking and texting. Task-management strategies are the changes initiated by

drivers to engage in mobile phone distraction. Scanning the environment more often was a

consistent strategy in the models, indicating that the decision to engage in mobile phone use is

closely related to the perception of potential hazards. Scanning for police officers was also

significant in talking and texting/browsing tasks. The present findings seem to support other

research studies in Queensland (White, et al., 2010), which report that infrequent distracted

drivers were more likely to report that police presence and risk of an accident would prevent

them from using their mobile phone while driving. Appropriate caution should be exercised in

the interpretation of this finding because there is no guarantee that the drivers’ judgement of a

driving situation is adequate to minimise crash risk (Huth & Brusque, 2014; Kircher &

Ahlstrom, 2016).

Several studies have used Theory of Planned Behaviour (TPB) constructs, and extended

versions of it, to explain mobile phone distracted driving decisions in Australia (Gauld, Lewis,

& White, 2014; Gauld, et al., 2016b; Nemme & White, 2010; Waddell & Wiener, 2014; White,

et al., 2010) and internationally (Chen, Donmez, Hoekstra-Atwood, & Marulanda, 2016; Prat,

Gras, Planes, González-Iglesias, & Sullman, 2015). The model consists of three standard

constructs: Attitude, Subjective Norm (SN), and Perceived Behavioural Control (PBC), the

strength of which determine the strength of one’s intentions toward engaging in the behaviour,

which are then regarded as proxies for whether people will actually engage in the behaviour

(Lennon, Oviedo-Trespalacios, & Matthews, 2017). Among the behavioural beliefs, high

intenders (i.e. a high intention to use a mobile phone while driving) were more likely to see

‘sharing information’ and ‘using time effectively’ as positive outcomes of concealed texting

while driving than low intenders (Gauld, et al., 2014). In the case of SN, Nemme and White

(2010) found that the more a person believes that their peers approve of and engage in

behaviours such as texting while driving, the greater their intention to engage in these

behaviours. In a recent NSW study, PBC has been found to be the strongest contributor to

drivers’ intentions to use hand-held mobile phones (Waddell & Wiener, 2014). Overall, results

of the present study provide considerable support for the efficacy of the TPB model in


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understanding mobile phone distracted driving. Other variables such as perceived crash risk has

been less successful at explaining distracted driving (Walsh, et al., 2008).

Investigations have been conducted to identify the beliefs influencing young drivers (17 – 25

years) to initiate, monitor/read, and respond to social interactive technology (e.g., Facebook,

email, texting) on smartphones, to target in public education messages (Gauld, Lewis, White,

Fleiter, & Watson, 2017; Gauld, Lewis, White, & Watson, 2016a; Gauld, et al., 2016b). For

example, Gauld et al. (2016a) found that young drivers reported that contact via mobile phone

was important to them while driving, so they could keep up to date with friends’ plans,

particularly when a meeting was planned. Some drivers also referred to the pressure they felt

from friends who expected a very quick reply and who would send continual communications

until they received a response.

4.4 RELATIONSHIP BETWEEN MOBILE PHONE USE AND DRIVING PERFORMANCE

Two main approaches are utilised in the scientific literature to study driving performance of

mobile phone distracted drivers: on-road and/or laboratory observations. On-road observations

comprise naturalistic and quasi-naturalistic studies that allow for seeing the driver’s behaviour,

in uncontrolled or controlled environments, respectively. Laboratory observations have been

consolidated in road safety research, as a low risk and economically feasible option for studying

driving behaviours while controlling for different factors (Collet, Guillot, & Petit, 2010).

Various authors have developed important safety evaluation methods based on naturalistic and

simulated driving behaviour observations. Traditionally, driving simulators are considered the

principal tool for road safety laboratory research. Driving simulators have been developed using

advances in computer technology and nowadays are cheaper and safer than in-vehicle or on-

road testing (Ariën et al., 2014). Nonetheless, with new technological developments in in-

vehicle driving monitoring, naturalistic studies have increased their presence in the mobile

phone distracted driving literature.

Generally, in simulator studies, it is possible to observe crashes. Although intuitively, the best

option for studying crashes would be a controlled environment such as simulators, difficulties

arise because crashes are rare events (Svensson & Hydén, 2006). For this reason, the use of

surrogate safety measurements as a way of studying driving performance has been a frequent

practice in the mobile phone distracted driving literature. These surrogate measures include:

acceleration, headway distance, lane position, speed, among others. Yan, Abdel-Aty, Radwan,

Wang, and Chilakapati (2008) validated a set of surrogate measures for evaluating safety in

signalised intersections through the contrast of crash reports and simulator data. These surrogate

measures included speed in different instances while approaching the intersection, acceleration,

stop decision, and headway distance (for the case when the car is following another). As a result,

previously accepted risky parameter levels of speed, acceleration, and headway were associated

with high rear-end risk zones.


FINAL REPORT 17

This section reviews research in mobile phone distracted driving and driving behaviour change

from two perspectives: (1) Impaired driving behaviour, including changes in driving

performance that are traditionally associated with higher crash risk. (2) Self-regulation,

including potential safe behaviours that drivers perform to integrate the mobile phone tasks into

driving.

4.4.1 DRIVING BEHAVIOUR CHANGE

Recent literature on mobile phone distracted driving has examined various driving performance

metrics such as speed, acceleration, lane position, and headway distance (Oviedo-Trespalacios

et al., 2016).

The speed selection of drivers has been reported to be influenced by various types of mobile

phone tasks, including conversation (Becic et al., 2010, Metz et al., 2015, Yannis et al., 2010,

Tractinsky et al., 2013, Reimer et al., 2011), holding a mobile phone (Christoph et al., 2013),

navigation (Christoph et al., 2013), reading (Rudin-Brown et al., 2013), reaching for a mobile

phone (Christoph et al., 2013), texting (McKeever et al., 2013, Thapa et al., 2014), answering

by pressing the send button (Tractinsky et al., 2013), and dialling (Tractinsky et al., 2013).

While a majority of studies reported a decrease in speed selection under mobile phone distracted

driving (Oviedo-Trespalacios et al., 2017b, Oviedo-Trespalacios et al., 2017a, Oviedo-

Trespalacios et al., 2015), some reported an increase in speed for mobile phone conversation

(Garrison and Williams, 2013, Liu and Ou, 2011, Stavrinos et al., 2013), and texting (Young et

al., 2014, Rudin-Brown et al., 2013). Speed variability has been reported to increase if the

conversation includes emotional components (Dula et al., 2011). A study matching self-

reported behaviour and observed driving performance found that drivers who reported frequent

use of a mobile phone while driving changed speed more rapidly with faster throttle

accelerations, and sudden non-directional accelerations (Zhao et al., 2013). Platten et al. (2013)

reported that distracted drivers approaching hazardous situations decreased speed rapidly with

higher decelerations.

Distracted drivers have been reported to have less lane deviation while conversing (Garrison

and Williams, 2013, Reimer et al., 2014) but an increased deviation while texting (McKeever

et al., 2013, Rudin-Brown et al., 2013) compared to non-distracted drivers. Many studies,

however, have reported a negligible difference in lane position between the baseline and the

distractive conditions of talking and texting (Cao and Liu, 2013, Irwin et al., 2015, Young et

al., 2014). In terms of headway distance maintenance, distracted drivers have been reported to

maintain a longer following distance (Bergen et al., 2013, Yannis et al., 2010) while talking

and to have more gap variations (He et al., 2014) while texting. Pouyakian et al. (2013) reported

that drivers answer mobile phone calls more frequently when headway distance is greater than

25 m.

Mobile phone use while driving impairs the interactions between driver and vehicle. Steering

wheel corrections were higher among drivers distracted by a mobile phone (Zhao et al., 2013),

particularly with conversations (Garrison and Williams, 2013) and texting (Owens et al., 2011).


FINAL REPORT 18

The ability to maintain a constant speed decreases significantly when a driver is texting (Choi

et al., 2013a); however, this result contradicts other research that reported a negligible effect of

mobile phone conversations on speed maintenance (Cao and Liu, 2013, Reimer et al., 2012) or

distraction due to drivers preparing to attend an incoming call (Holland and Rathod, 2013). The

braking task has also been reported to be affected by mobile phone tasks. Distracted drivers

brake aggressively when approaching an obstacle (e.g. pedestrian crossing) along the road

(Haque and Washington, 2014a, Berg and Dessecker, 2013). Compared to hands-free driving,

drivers conversing using a hand-held phone tend to brake more frequently (Zhao et al., 2013).

Interestingly, there is a consensus that braking time of distracted drivers increases with

conversing (Kim et al., 2013, Rossi et al., 2012, Benedetto et al., 2012, Berg and Dessecker,

2013, Long et al., 2012, Bergen et al., 2013), texting (Leung et al., 2012, He et al., 2014, Long

et al., 2012), dialling (Platten et al., 2013), and ringing (Zajdel et al., 2013).

Eye behaviour (i.e., blink rate, gaze concentration, gaze position, etc.) has been utilised as a

proxy for capture of critical information from the surrounding road traffic environment under

distraction. Drivers distracted by mobile phone conversations have been reported to have an

increased gaze concentration, implying less peripheral awareness and detection sensitivity

(Reimer et al., 2012). In particular, mobile phone distractions lead to a decrease in vertical and

horizontal glances (Briggs et al., 2011, Reimer et al., 2012). Mobile phone tasks such as

reaching, answering, dialling, texting, and browsing were found to be associated with longer

off-road glances (Simons-Morton et al., 2014), with texting tasks requiring more frequent and

longer off-road glances (Owens et al., 2011, Reimer et al., 2014, Young et al., 2014, Tivesten

and Dozza, 2014) and emotionally involving mobile phone conversations leading to a pattern

of visual tunnelling with a decline in visual fixations (Lansdown and Stephens, 2013).

Mobile phone use while driving modifies the decisions made by drivers in certain traffic

interactions. Drivers distracted by mobile phone conversations have been reported to take a

longer time to detect a pedestrian at a zebra crossing (Haque and Washington, 2014b),

indicating not only impaired peripheral scanning behaviour but also a slow information

processing ability. Garrison and Williams (2013) noted that distracted drivers paid more

attention to driving-relevant objects compared to less relevant objects like billboards, indicating

a strategic decision by drivers to manage the human-environment interactions. Haque et al.

(2016) reported that drivers conversing on a mobile phone while driving reduce their safety

margins and manoeuvrability of the vehicle in complex traffic conditions such as roundabouts.

Additionally, drivers distracted by mobile phone conversations committed more driving errors

and road violations, e.g. road lanes excursions, speeding, red light running (Nabatilan et al.,

2012). In contrast, Dula et al. (2011) and Platten et al. (2013) have not found any significant

difference in the number of traffic light infractions for conversation tasks.

Interference is a two-way phenomenon in which both the driving task and the mobile phone

task are perturbed. Becic et al. (2010) reported that performing dual tasks like driving while

talking over a mobile phone influences both driving performance and conversation including

quality loss in speech comprehension, language encoding and language production. Other


FINAL REPORT 19

effects on conversation include loss of quality in speech production, complexity (Atchley et al.,

2011) and rhythm (Maciej et al., 2011). Cao and Liu (2013) reported that concurrent vehicle

lane keeping and speech comprehension tasks did not affect lane keeping performance but the

performance of a comprehension task was reduced. Spence et al. (2013) reported a loss of

accuracy in conversation when distracted drivers were assigned a demanding cognitive task.

Driving task has also been reported to influence texting performance with an increase in

accuracy errors (Alosco et al., 2012) and response times (He et al., 2014).

A large body of the literature focuses on performance differences between hand-held and hands-

free conversations. Brace et al. (2007) and McCartt et al. (2006) concluded that hand-held

dialling leads to less safe driving as well as faster but inaccurate dialling of mobile phones.

Horrey and Wickens (2006) and Caird et al. (2008) showed that the impairment of driving

performance for a hands-free phone conversation is equivalent to that experienced as the result

of an in-vehicle conversation. Svenson and Patten (2005) argued that the position of the mobile

phone in the car could interfere with the in-vehicle tasks and needs to be investigated. Haque

and Washington (2014b) and Benedetto et al. (2012), however, did not find any significant

difference in reaction times to unexpected events between hand-held and hands-free mode. The

effects of other phone characteristics like the size and type of the mobile phone on driving

performance are usually not available in the literature (McCartt et al., 2006).

4.4.2 SELF-REGULATION

Drivers initiate changes in driving to integrate the secondary task. While engaged in

uninterrupted mobile phone conversations, drivers reduced their driving speed in similar

driving conditions. This is confirmed by naturalistic studies (Fitch et al., 2014, Fitch et al.,

2017), experimental investigations (Tractinsky et al., 2013, Horberry et al., 2006), and self-

reported experiences (Young and Lenné, 2010, Huth and Brusque, 2014) corroborating that

mobile phone distracted driving, and particularly engaging in conversation, results in drivers

decreasing their driving speed. Reduced speed could offer safety advantages in terms of crash

likelihood or injury severity. For instance, Aarts and Van Schagen (2006) found that crashes

increase at an exponential rate with the speed increase of individual vehicles. Nonetheless, the

potential negative consequences of this speed reduction of distracted drivers are that it could

increase the risk of nose-to-tail crashes and congestion.

Under a complex driving environment with a narrower lane, high speed limit, and frequent

presence of intersections and roadside buildings, drivers distracted by mobile phone

conversations were reported to select a lower driving speed with higher variability and higher

lateral acceleration (Liu and Ou, 2011). Demanding driving scenarios like driving along windy

roads and driving in heavy traffic have been reported to influence driving speed and lane

position variability of mobile phone distracted drivers (Tractinsky et al., 2013, Oviedo-

Trespalacios et al., 2017b, Oviedo-Trespalacios et al., 2017a). Becic et al. (2010) reported that

drivers under mobile phone distracted driving prioritize the driving task over the secondary task

depending on the complexity (i.e., straight road segment or intersection) of the road traffic


FINAL REPORT 20

environment. The speech production of the drivers engaged in mobile phone conversations has

been reported to decrease when the difficulty of driving increased (Becic et al., 2010).

Tractinsky et al. (2013) found that driving along windy roads and heavy traffic resulted in a

delayed response to attend incoming calls; additionally, in complex situations drivers showed

less willingness to initiate or accept incoming phone calls. Similarly, Atchley and Chan (2011)

argued that drivers using the mobile phone may increase their vigilance even when driving in

less stimulating environments.

Using as a basis the seminal work of Young and Regan (2013), this review considers tactical

decisions of drivers to engage in mobile phone distracted driving. Tactical self-regulation

corresponds to the decision that drivers make about when or where to engage in mobile phone

distracted driving. Oviedo-Trespalacios et al. (Under Review-c) demonstrated that a driver’s

decisions to engage in multitasking can vary from location to location. While driving in a

controlled environment, drivers showed a preference for engaging in mobile phone use at times

when the vehicle was stopped, e.g. waiting at a signalised intersection (Oviedo-Trespalacios et

al., Under Review-a). Confirming the existence of tactical self-regulation has important

implications for police enforcement and road safety research. Knowing where drivers prefer to

engage in unlawful mobile phone use could help to support and optimise police enforcement.

Additionally, there is a need for making fair comparisons in the estimations of crash risk due to

mobile phone distracted driving. The decision-making process of drivers should be included in

risk assessment activities (e.g. to match baselines and mobile phone use while driving

sequences on a scenario basis as suggested by Tivesten and Dozza (2014).

4.5 RELATIONSHIP BETWEEN MOBILE PHONE USE WHILE DRIVING AND CRASH RISK

In the context of mobile phone distracted driving, crash data is acknowledged as the key

performance measure for safety in the traffic system (Oviedo-Trespalacios et al., 2016). The

provision of ongoing and reliable crash data is a key component of evidence-based road safety

practice. Crash data is usually provided by government-related entities; perhaps the most

common source is crash reports (e.g. police or health-care providers). Generally, crash police

or hospital data related to mobile phone distraction has a series of limitations: the under-

reporting of low severity crashes, low occurrence of crashes linked to mobile phone use, and

lack of behavioural detail preceding the crash. Therefore, it is reasonable to argue that crash

data should not serve as a unique and standalone tool for informing evidence-led initiatives in

mobile phone distracted driving. A common issue in the U.S. is that a large proportion of

crashes that are reported to involve distraction do not have a specific behaviour or activity

listed; rather they specify “distraction/inattention details unknown” (NHTSA, 2016).

There are alternatives for overcoming the limitations of police or hospital mobile phone

distraction crash data: First, complement crash data with vehicle technologies (apps and

devices) for driving monitoring (Singh, 2001) and, exceptionally, other external sources

considered in police reports, such as cameras or witnesses. This is the rationale behind

naturalistic studies whereby a group of drivers are monitored until a crash of interest is


FINAL REPORT 21

registered. Second, in the case of a non-fatal injury, self-reported data, including questionnaires

or interviews, could explain crash circumstances. Although self-reported data suffers from

several drawbacks related with human factors such as memory or social desirability bias, recent

research suggests that self-report data is fairly consistent with the actual police records in

Australia (Ivers et al., 2009) and objective driving observations (Zhao et al., 2012).

4.5.1 POLICE AND HOSPITAL DATA RELATED TO CRASH RISK

Mobile phone distracted driving studies using police and hospital data are scarce worldwide.

Based on crash reports in Australia (NSW), a study conducted 15 years ago by Lam (2002)

showed that there was no significant increase in the risk of being killed or injured in a crash for

drivers using a hand-held phone in most age groups, except 25–29 year-old drivers, when

compared with those drivers who crashed without any distraction. The risk of car crash injury

for 25–29 year-old drivers who used a hand-held phone was estimated to be 2.4 times higher

than those not being distracted. Based on crash reports in the U.S., it is believed that distracted

driving (included mobile phone use) caused nearly 3,477 fatalities in 2015 alone (NHTSA,

2017). A U.S. study of police crash reports reported that mobile phone distraction is estimated

to have resulted in 18% of fatal crashes and 5% of injury crashes (Overton et al., 2014). A study

targeting young drivers in the U.S. found that drivers had a higher likelihood of being severely

injured if they were distracted by a cell phone (Neyens and Boyle, 2008). In Canada, Asbridge

et al. (2013) reported that the odds of a culpable crash increase by 70% when the driver is using

a mobile phone.

4.5.2 NATURALISTIC OBSERVATIONS RELATED TO CRASH RISK

Naturalistic driving studies are methods utilised for investigating driver behaviour and traffic

safety in the roads. However, these methods have important limitations for the study of risk in

mobile phone distracted driving: (i) the number of crashes observed in naturalistic driving

studies is typically small, (ii) there is confounding bias arising from other driver behaviour

errors (e.g. speeding), and (iii) the environment/conditions of a safety-critical event is

uncontrolled (Young, 2017, Oviedo-Trespalacios et al., 2016). These limitations hinder the

generalisability of the research findings to the population of distracted drivers.

Besides these technical challenges and academic debate, naturalistic studies have reported

strong associations between crash risk and mobile phone use while driving. The most recent

and largest naturalistic study in the U.S., Second Strategic Highway Research Program

Naturalistic Driving Study (SHRP 2 NDS), gathered information from more than 3,500 drivers

across a 3-year period (Dingus et al., 2016). Overall, the SHRP 2 NDS has reported that any

hand-based mobile phone interactions increase crash risk odds by a factor of 3.6. An odds ratio

value of 1.0 is considered equivalent to driving while not distracted. Table 4.2 shows the

increases in the odds of a crash according to mobile phone tasks detected:


FINAL REPORT 22

Table 4.2 Crash risk associated with mobile phone use

Observed distraction Odds ratio (95% CI)

Mobile phone browse 2.7 (1.5 – 5.1)*

Mobile phone handheld dial 12.2 (5.6 – 26.4)*

Mobile phone reach 4.8 (2.7 – 8.4)*

Mobile phone handheld text 6.1 (4.5 – 8.2)*

Mobile phone handheld talk 2.2 (1.6 – 3.1)*

Mobile phone handheld total 3.6 (2.9 – 4.5)*

*indicates a difference at the .05 level of significance

Adapted from Dingus et al. (2016)

These results have been under discussion, but are not yet considered to be conclusive. Recently

Young (2017) discusses potential confounding bias arising from driver behaviour errors and a

mismatch in additional secondary task between the exposed and unexposed drivers. This means

that usually drivers who crash while using their mobile phones were simultaneously engaging

in other risky driving behaviours such as speeding. Since videos of driving while not distracted

by the mobile phone also lacked the other risky driving behaviours observed in the crash, it is

argued that they do not constitute a suitable comparison on which to determine the unique effect

of mobile phone distraction.

An important finding reported in the SHRP 2 NDS is that young drivers (16 – 20 years old) and

older drivers (65 – 98 years old) have higher crash risks while using a mobile phone (Guo et

al., 2017).

Another important naturalistic study was conducted in the U.S. by Fitch et al. (2013). In this

naturalistic study, a total of 204 drivers were monitored between February 2011 and November

2011. Crash risk was calculated using safety critical events that comprised crashes, near-

crashes, and crash-relevant conflicts. The results are shown in Table 4.3:

No naturalistic study has been finalised to inform mobile phone distracted driving issues and

particularities in Australia. At the moment, data from the first large-scale Australian Naturalistic

Driving Study (NDS) (Regan et al., 2013) is under analysis. It is unclear when the data will be

publicly available.

Table 4.3 Crash risk associated with mobile phone use

Observed distraction Odds ratio (95% CI)

Mobile phone Visual-Manual Subtasks (i.e. text

messaging/browsing, locate/answer, dial, push to begin/end

use, and end handheld phone use)

1.73 (1.12 – 2.69)*


FINAL REPORT 23

Mobile phone handheld talk 0.79 (0.43 – 1.44)

Mobile phone portable hands-free talk 0.73 (0.36 – 1.47)

Mobile phone integrated hands-free talk 0.71 (0.3 – 1.66)

*Indicates a difference at the .05 level of significance

Adapted from NHTSA (2016 and Fitch et al. (2013

Based on the recent Visual-Manual NHTSA Driver Distraction Guidelines for Portable and

Aftermarket Devices (NHTSA, 2016) and a meta-analysis of naturalistic studies conducted by

Simmons et al. (2016), two main findings have been consistent in the naturalistic driving

literature:

(i) Visual-manual tasks, such as texting and browsing, were associated with

increased crash risk and safety-critical events (see Dingus et al. (2006),

Dingus et al. (2006), Hickman et al. (2010), Hickman and Hanowski (2012),

Simons-Morton et al. (2014), Simmons et al. (2016), Oviedo-Trespalacios et

al. (2016), and Fitch et al. (2017), for some supportive literature) .

(ii) Non-visual-manual tasks, such as conversing, were not associated with

increased crash risk and safety-critical events (see Klauer et al. (2006), Olson

et al. (2009) Hickman et al. (2010), Oviedo-Trespalacios et al. (2016),

Young (2017), and Oviedo-Trespalacios et al. (2017) for some supportive

literature). These results confirm that there are no differences in crash risk

between hand-held and hands-free conversations (see Fitch et al. (2013), and

Oviedo-Trespalacios et al. (2016) for supportive literature). Though

speaking or listening to a hand-held device in isolation did not appear to

increase safety-critical event risks (e.g. crashes), talking does require the

driver to first locate, reach for and make a call on or answer the hand-held

device. These task sub-components of hand-held mobile phone

conversations could entail highly intensive visual, cognitive, and manual

interactions (e.g. dialling or battery/duration monitoring) which increase

crash risk.

An important consideration is that the most recent article published by Dingus et al. (2016)

reported that talking could more than double crash risk in mobile phone distracted driving.

There has been significant academic debate generated by these results, with the method of

calculating the odds ratios being called into question. Since conversing on a phone at the time

of a crash often coincides with other factors that contribute to crash occurrence, the contribution

made by use of the phone is difficult to determine; one method of calculating the odds ratios

ignores the impact of other factors, and indicates increased risk, while another (which is

contested) takes the other factors into account and does not indicate increased risk from

conversation alone. The debate has yet to be resolved, and has important policy implications

for the management of cognitive distraction (see Atchley et al. (2017) and Strayer et al. (2003)).


FINAL REPORT 24

While it is not completely clear why cognitive distraction (e.g. talking on a mobile phone)

would not increase crash risk in naturalistic studies (bearing in mind the contrary findings of

Dingus et al., 2016), recent research has suggested that the distraction observed in controlled

studies of conversing on a mobile phone could be a result of not allowing participants to engage

in natural behavioural adaptations such as self-regulation (Oviedo-Trespalacios et al., 2017).

4.5.3 EXPERIMENTAL OBSERVATIONS RELATED TO CRASH RISK

Experimental and/or naturalistic studies, on the other hand, are not suitable for estimating actual

crash risk as crashes are rarely observed within the study design (Caird et al., 2008). Among

the few studies that have discussed safety, mobile phone tasks like dialling (Tractinsky et al.,

2013), and texting (Alosco et al., 2012, Kim et al., 2013, Stavrinos et al., 2013, Bendak, 2014)

have been reported to increase the frequency of crashes.

4.5.4 SELF-REPORTED DATA RELATED TO CRASH RISK

A case crossover study in Australia using hospital data showed that drivers who use a mobile

phone up to 10 minutes before a crash are associated with a fourfold increase in the likelihood

of having a serious crash (McEvoy et al., 2005). In a study using drivers who attended hospital

in Australia (WA), a distracting activity (not only mobile phone use) was cited in 57% of all

rear-end collisions in which the driver hit the vehicle in front (McEvoy et al., 2007). Another

case crossover study in Canada, using actual telephone activity of drivers reporting a crash,

found that mobile phone conversations increase crash risk by a factor of four (Redelmeier and

Tibshirani, 1997). In Norway, a study using self-reported data of drivers involved in accidents

reported that the crash risk of using hand-held phones is higher than using hands-free

technology (Backer-Grøndahl and Sagberg, 2011).

4.6 MOBILE PHONE USE WHILE DRIVING AND REGULATORY APPROACHES

Efforts to combat distracted driving today should involve system-wide stakeholders from

community advocacy groups, mobile phone technology developers, car manufacturers, and

researchers, among others. At first glance, a combination of a definitive mobile phone ban while

driving and strong enforcement should be the most effective approach to address this problem.

However, research worldwide showing a large prevalence of mobile phone distracted driving

has confirmed that legislation and enforcement are not necessarily preventing mobile phone use

while driving. As noted earlier, pioneers and advanced road safety systems with strong laws on

distracted driving such as Australia and the USA have been unsuccessful in stopping these

behaviours. The partial success of these strategies confirms the need for enhancing our

understanding of the nature of the distraction problem.


FINAL REPORT 25

4.6.1 LEGISLATION

Traditionally, legislation on distraction has focused too heavily on the role of the driver, while

ignoring the responsibility of the wider road transport system (Young and Salmon, 2015,

Parnell et al., 2017). This approach is lacking because mobile phone distraction is a complex

problem that requires the unified and consistent action of multiple stakeholders from across the

transport system (e.g. mobile phone manufacturers, app designers, vehicle manufacturers, etc.).

System-wide legislation and interventions will allow more opportunities to prevent crashes and

injuries.

The report “Mobile phone use: a growing problem of driver distraction” published by the World

Health Organisation (WHO, 2011) showed that in many countries, legislation already plays an

important role in addressing driver distraction behaviour (see Appendix B for some examples).

For instance, European countries have general laws that target driving “without due care and

attention”. However, it seems that there is also an increasing trend towards development and

adoption of more specific legislation relating to particular mobile phone tasks or population

groups. In the U.S., many states explicitly prohibit talking, text-messaging or playing video

games on hand-held mobile phones while driving. Additionally, a number of states, such as

California, have passed laws banning or restricting young drivers (under the age of 18) from

using mobile phones, or other types of mobile devices while driving (Zhou and Curry, 2009).

Based on data from the National High Traffic Safety Administration (NHTSA) (2016) currently

46 states, District of Columbia (DC), Puerto Rico, Guam, and the U.S. Virgin Islands ban

texting while driving for drivers of all ages. Fourteen states, DC, Puerto Rico, Guam, and the

U.S. Virgin Islands ban hand-held mobile phone usage while driving. It is also important to

mention that all states with device bans allow emergency calls, and some allow talking while

stopped in traffic.

Generally, the effectiveness of legislation has been low if not virtually non-existent. The most

recent literature review analysing a total of eleven peer-reviewed articles and reports from the

U.S. on the impact of mobile phone restrictions for young drivers confirmed that nearly none

of the restrictions evaluated before 2014 appear to have a long term effect on the prevalence of

mobile phone use by novice drivers (Ehsani et al., 2016). Although some general studies in

Washington DC, New York, and Connecticut have reported that hand-held bans could have

long term effects (if effective enforcement is available), this could be because many drivers

may have switched to hands-free devices (McCartt et al., 2010b). Recently, a U.S. study

conducted by Rudisill and Zhu (2017) using the 2008–2013 National Occupant Protection Use

Survey (NOPUS), concluded that universal bans of hand-held mobile phone use while driving

were associated with markedly lower hand-held phone conversations across all drivers.

However, mobile phone use was higher overall among females, younger age groups, and

African American drivers; as such, these groups may benefit from directed interventional

efforts. In New Zealand, an evaluation of the 2009 law that banned hand-held mobile phone

use while driving showed evidence of some partial success in the on-road prevalence of mobile

phone use. Similar results were documented in the U.K. by Johal et al. (2005).


FINAL REPORT 26

A review of the research on the effects of driver mobile phone usage bans (particularly texting)

found mixed results (McCartt et al., 2014). Policy evaluation of the effect of legislation

prohibiting visual-manual interactions such as texting has been difficult. Among other issues,

estimating the prevalence of texting interactions while driving is challenging because drivers

usually hide the mobile phone through behavioural adaptions (e.g. texting with the phone in

their lap) (Vera-López et al., 2013). Recently, these behavioural adaptations have been reported

in Australia by Oviedo-Trespalacios et al. (In press). Nonetheless, the high prevalence of visual-

manual mobile phone interactions reported in self-reported and observational on-road studies

confirm that this is a persistent issue regardless of legislation. In Europe, Jamson (2013)

documented that drivers in the most highly regulated country (Italy) report texting as frequently

as those in countries with no legislation.

The impact that mobile phone bans has on reducing crash risk has been widely discussed. Some

studies have found that driver mobile phone bans do not reduce collisions. For example, in the

city of San Antonio (TX), after a prohibition from January 2015 of portable electronic devices

(mobile phones, music players, electronic reading devices, computers, GPS or navigation

systems, or portable gaming devices) while driving, no positive effect in reducing the number

of accidents was found within the city (Roper, 2017). One reason that could explain why San

Antonio’s hands-free law has had no effect on the reduction of mobile-device related accidents

might be that people are texting below eye-level or in their laps, to conceal their activity, making

it much more dangerous to engage in, rather than texting with the device near eye level.

Research elsewhere has demonstrated that these mobile phone positions are not optimal and

increase the visual workload (see Wittmann et al. (2006) and Alconera et al. (2017)).

There are, however, some notable success stories. In California (U.S.), Kwon et al. (2014)

reviewed the effect of the hand-held mobile phone ban in July 2008 using a large-scale traffic

accident database. The results confirmed that the hand-held mobile phone law showed a primary

effect on decline of collisions involving mobile phone distracted driving. Additionally,

Ferdinand et al. (2014) found, using data in 2000 through 2010 in 48 U.S. states, that primarily

enforced laws banning all drivers from texting were significantly associated with a 3%

reduction in traffic fatalities in all age groups, and those banning only young drivers from

texting had the greatest impact on reducing deaths among those aged 15 to 21 years. It is

important to mention that most of the research agrees that there are large differences in the

effect of the law between jurisdictions (Rocco and Sampaio, 2016). Altogether, it is important

to remember that these studies based on crash data are unable to provide a causal link between

the ban and fatalities.

In Australia, to the knowledge of the authors, no comprehensive evaluations have been

conducted to assess the effectiveness of mobile phone distracted driving legislation.

4.6.2 ENFORCEMENT

Hand-held mobile phone bans require strong enforcement to have the desired effect on driver

behaviour in the long term (McCartt and Hellinga, 2007, McCartt et al., 2010a). However,


FINAL REPORT 27

research has shown that enforcing these laws is difficult. A comprehensive qualitative study

with police officers found that barriers to enforcement in the U.S. include (Nevin et al. (2016)):

- Societal factors: (i) Distracted driving law is difficult to enforce because this is usually

directed to specific tasks such as texting and drivers could be using their phone for

utilitarian systems such as GPS; and (ii) mobile phones are technologies in constant

evolution sometimes faster than policy cycles.

- Organisational factors: (i) Distracted driving has usually low prioritisation compared

to other policing functions, (ii) lack of resources dedicated to distraction; and (iii) lack

of clear policies regarding distracted driving among officers.

- Interpersonal factors: (i) Many drivers challenge officers during traffic stops; and (ii)

communications between officers can influence enforcement motivations.

- Individual factors: (i) Officers identify with distracted drivers and distracted

behaviour; (ii) detection of distracted drivers is difficult, and (iii) some officers believe

that drivers can safely multi-task.

In the U.S., high-visibility enforcement programs targeting drivers who use hand-held mobile

phones have been trialled successfully. Observed hand-held mobile phone use dropped nearly

33% in California and Delaware (NHTSA, 2016). The high-visibility operation in NSW, known

as Operation Compliance, was highlighted by the World Health Organisation (WHO, 2011).

Operation Compliance requires all police, regardless of duty type, to target specific traffic

safety offences such as the use of mobile phones. To this end, resources are used to maximize

effect – e.g. the use of motorcycle units to detect the use of hand-held phones by drivers – where

the elevated position of the rider allows for the interior of the vehicle to be more clearly

observed, and texting drivers to be detected. To the best of the authors' knowledge, no

evaluation of the Operation Compliance has been conducted examining changes in mobile

phone distracted driving prevalence.

In Queensland, the high self-reported prevalence of mobile phone use suggests that an

enforcement oriented policy has not been able to prevent mobile phone distracted driving

(Oviedo-Trespalacios et al., In press). For instance, drivers reported scanning the environment

and covering the phone all the time with their hand to avoid police. The fact that drivers learned

that covering the phone with their hand will help them avoid a police offence while driving

must be incorporated in planning for road safety strategies. More research in behavioural

adaptation is needed to overcome the limitations of today’s interventions.


FINAL REPORT 28

5 REVIEW OF CURRENT REGULATORY AND ENFORCEMENT PRACTICES

5.1 BACKGROUND

Australian State transport agencies and police agencies share responsibility for policy

formulation and advice that is translated into regulatory frameworks for controlling the use of

mobile phones and other mobile technologies by drivers. The regulatory framework also sets

out penalties, while enforcement of the regulations is the responsibility of police. While there

is a great deal of commonality between regulation and enforcement approaches across

Australian States, there are also differences. Such differences are arguably more likely to be

evident in an area of emerging concern, where State-specific political factors may influence the

underlying policies applied to driver distraction by mobile phones and the form of the

regulations that operationalise the policies, with flow-on effects on the way that police conduct

enforcement. The purpose of this part of the project was to examine current regulatory and

enforcement practices across Australia, to identify the policy goals being addressed, and to

discern the degree of commonality in the policy goals. This was achieved through a review of

publicly available policy documents and in the consultations with transport authorities and

police.

5.2 AUSTRALIAN ROAD RULES REGULATION 300

The Australian Road Rules form the basis of most road law in Australia, although jurisdictions

are able to choose whether or not they will adopt particular rules, and can add their own rules

or modify the model rule. Jurisdictions also define their own offences and penalties based on

the rule.

The relevant Australian Road Rule is Regulation 300 - Use of Mobile Phones (ARR 300), which

states:

(1) The driver of a vehicle must not use a mobile phone while the vehicle is moving, or

is stationary but not parked, unless—

(a) the phone is being used to make or receive an audio phone call and the body

of the phone—

(i) is secured in a mounting affixed to the vehicle while being so used; or

(ii) is not secured in a mounting affixed to the vehicle and is not being

held by the driver, and the use of the phone does not require the driver,

at any time while using it, to press any thing on the body of the phone or

to otherwise manipulate any part of the body of the phone; or


FINAL REPORT 29

(ab) the phone is being used as a driver's aid and—

(i) the body of the phone is secured in a mounting affixed to the vehicle

while being so used;

and

(ii) the use of the phone does not require the driver, at any time while

using it, to press any thing on the body of the phone or otherwise to

manipulate any part of the body of the phone; or

(b) the vehicle is an emergency vehicle or a police vehicle; or

(c) the driver is exempt from this rule under another law of this jurisdiction.

ARR 300 then notes that certain terms are defined elsewhere and gives examples of driver’s

aids: closed-circuit television security cameras; dispatch systems; navigational or intelligent

highway and vehicle system equipment; rearview screens; ticket-issuing machines; and vehicle

monitoring devices.

Since the aim of allowing hands-free phone use is to address the manipulation and direction-

of-gaze issues associated with hand-held phones, ARR 300 then outlines what requirements

must be met:

(2) For the purposes of this rule, a mobile phone is secured in a mounting affixed to the

vehicle if, and only if—

(a) the mounting is commercially designed and manufactured for that purpose;

and

(b) the mobile phone is secured in the mounting, and the mounting is affixed to

the vehicle, in the manner intended by the manufacturer.

(3) For the purposes of this rule, a driver does not use a phone to receive a text message,

video message, email or similar communication if—

(a) the communication is received automatically by the phone; and

(b) on and after receipt, the communication itself (rather than any indication

that the communication has been received) does not become automatically

visible on the screen of the phone.

(4) In this rule—

"affixed to", in relation to a vehicle, includes forming part of the vehicle;


FINAL REPORT 30

"audio phone call" does not include an email, text message, video call, video message

or other similar communication;

"body", in relation to a mobile phone, means the part of the phone that contains the

majority of the phone's mechanisms;

"held" includes held by, or resting on, any part of the driver's body, but does not include

held in a pocket of the driver's clothing or in a pouch worn by the driver;

"mobile phone" does not include a CB radio or any other two-way radio;

"use", in relation to a mobile phone, includes any of the following actions by a driver—

(a) holding the body of the phone in her or his hand (whether or not engaged in

a phone call), except while in the process of giving the body of the phone to a

passenger in the vehicle;

(b) entering or placing, other than by the use of voice, anything into the phone,

or sending or looking at anything that is in the phone;

(c) turning the phone on or off;

(d) operating any other function of the phone.

What is evident in the level of detail and specification required is the need to adapt the

legislation to an increasing array of options presented by communications technologies.

The penalties to be applied to breaches of ARR 300 are set by individual jursidictions, which

can also exempt drivers (or particular kinds of drivers in particular circumstances) from the

rule. In the Australian Road Rules itself, there are general exemptions from any of the rules for

drivers of police vehicles and emergency vehicles, depending on the needs of the circumstances,

appropriate care being taken, and use of flashlights/alarm/siren.

5.3 JURISDICTION REGULATORY REQUIREMENTS

A search was performed on the public information supplied via websites of transport agencies

regarding laws about mobile phone use and the penalties applied. Where available, information

pertaining to other mobile or nomadic technology was included. This information was

confirmed or supplemented with information from interviews with transport and policing

agency representatives.

Table 5.1 summarises the information on the legal requirements in relation to ARR 300, and

the defined offences and penalties, where available. It also includes comments provided during

interviews relevant to potential legislative change.


FINAL REPORT 31

Table 5.1 Legislation and penalties for mobile phone use while driving

Fully licensed car drivers Other groups Comments arising from

interviews

ACT ARR 300, defines two

offences:

Drive using hand-held

mobile phone - $416 and 3

demerit points

Drive using mobile phone

for messaging, social

networking, mobile

application or accessing

the internet - $511 and 4

demerit points

Apparently no

differences

N/A

NSW ARR 300

$325 and 3 demerit points

Higher fine for use in school

zones: $433 and 3 demerit

points

Double demerit points on

public holidays

Complete ban

for P1/2 (P2

since Dec

2016)

Emerging issue of integration of

mobile phones with VDU, e.g.

Apple CarPlay: P drivers who

want to use legal functions (e.g.

music) may only be able to do so

through the phone interface

NT ARR 300


Complete ban

for P1/2

Total ban rejected due to

remote/regional needs

Qld ARR 300


Double demerit points for

second or subsequent offence

within 1 year

Complete ban

for P1

People low on points tend to

challenge to extend their time

SA ARR 300


Complete ban

for P1

Drivers do not understand the

legislation: think it’s legal to use

a hand-held when stopped in

traffic

Tas ARR 300


No

differences

Possibly penalties are not high

enough

Currently reviewing graduated

licensing

Monetary incentives likely to

work better, e.g. through

insurance

Vic ARR 300 Complete ban

for P1/2

Due to high noncompliance

among young people, examining


FINAL REPORT 32

$466 and 4 demerit points if there are ways of allowing

some use with particular kinds of

driver aid

Provide specific advice on

smartwatches

Emerging issue of technology

allowing phones to sync to car

and show Facebook etc

WA ARR 300, offences specified:

Using a hand held mobile

phone whilst driving

Creating, sending or

looking at a text message,

video message, email or

similar communication

whilst driving


No

differences

Public feedback is that penalties

should be increased

5.3.1 SIMILARITIES BETWEEN JURISDICTIONS

It is clear that all jurisdictions base their legislation on ARR 300, and comments made during

the interviews with transport and police agencies frequently referred to it. This implies that a

coordinated approach to legislation in this area has a high chance of success.

5.3.2 DIFFERENCES BETWEEN JURISDICTIONS

Given the universal use of ARR 300, the differences in the details of its application between

jurisdictions were greater than might have been expected.

5.3.2.1 Specification of offences

Most jurisdictions specify a single offence for mobile phone use, however ACT, NSW and WA

specify more than one.

NSW sets a larger fine for use of a mobile phone in a school zone.

WA specifies two offences, with texting, video messages and email being added to the generic

offence of “using a mobile phone while driving”. While the different offences recognise the

different tasks that can be performed using a mobile phone, as well as the overlap with ARR

299 (dealing with visual display units, or VDUs), there is no difference in penalties and it could

be considered that the additional offence is adequately covered by “using a mobile phone while

driving”.


FINAL REPORT 33

In the ACT an additional offence is also specified – “drive using mobile phone for messaging,

social networking, mobile application or accessing the internet” – but it has a higher fine and

an additional demerit point. This has the advantage of taking into account the greater risk

associated with non-conversing mobile phone tasks that draw attention away from the road for

more prolonged periods. There is potentially some value in adopting this approach, and

Queensland has indicated an interest in exploring the hierarchy of risks associated with different

kinds of mobile phone use.

As an aside, Victoria provides information about the penalties for using a smartwatch while

driving, but this does not involve the creation of a separate offence. Prepared by VicRoads in

response to inquiries from the public, the information explains how the provisions of ARR 299

and 300 apply to the use of smartwatches, which in any case operate via their connection with

a mobile phone.

5.3.2.2 Fines and demerit points/double demerit points

Across Australia, fines for mobile phone use (at the lower level for jurisdictions with more than

one offence) vary between $250 and $466, and the number of demerit points varies between 3

and 4. Double demerit points are assigned in some States, either on public holidays or (in

Queensland) for second and subsequent offences within a year. While a number of

considerations are taken into account in setting penalties, especially consistency across a

jurisdiction’s traffic penalties, the variation in the monetary penalty in particular seems high.

Similarly, double demerit points are applied to achieve greater deterrence under certain

circumstances that are presumed to be high risk, but for mobile phone use there is a lack of

consistency.

5.3.2.3 Young drivers

In some jurisdictions P1 and P2 drivers are completely banned from any form of mobile phone

use, in Queensland and SA the complete ban applies only to P1 drivers, and in the remainder

P1 and P2 drivers are treated in the same way as fully licensed drivers. It is worth noting that

the restrictions on P1/2 drivers fall under Graduated Driver Licensing (GDL) policy rather than

policy on driver distraction alone. GDL involves a mix of constraints on young driver exposure

to risk, and it is arguable that it is the overall balance of risk exposure that is more important

than risk in one area (i.e. mobile phone use) alone. However it is also desirable to pursue a

consistent policy line of distracted driving, and young drivers are simultaneously the group

most likely to regularly use a mobile phone, and the group with the highest crash risk.

5.4 ENFORCEMENT PRACTICES

Table 5.2 summarises the information provided by police agencies, and to some extent by

transport agencies, on the enforcement of mobile phone legislation. Only the Victoria Police


FINAL REPORT 34

did not respond, however information on enforcement in Victoria was provided by other

interviewees.

Table 5.2 Enforcement practices for mobile phone use while driving

Main enforcement

method

Other methods Comments

ACT Observation by car and

motorcycle police

Trialling unmarked

motorcycles with

uniformed police

Difficulty detecting texting

NSW Motorcycle police with

helmet cameras, also

working on congestion –

one squad CBD, another

at Parramatta,

occasionally use in rural

areas

Looked at camera

detection but requires

an operator as cannot

detect mobile phone

use automatically

Sometimes use spotter

from high vantage

point

Enforcement backed up with

campaigns e.g. Get Your

Hand Off It

Emerging issues: use of

phones increases, railway

crossing and stop sign

violations, use of navigation

systems creates problems if

vehicles are directed to

unsuitable roads

NT Visual observation by

police cars and

motorcycles, latter most

successful

Trialled cameras but

not successful

Difficulty detecting texting

Qld Observation and marked

and unmarked cars and

motorcycles

Sometimes use

observers. Wear body

cams, footage can be

used as evidence if

contested, which is

rare.

Typically not dedicated

mobile phone enforcement,

done as part of general duties

SA Motorcycle police with

Go-pro cameras, footage

can be used, but rarely

needed

Observers on high

vantage pint calling to

team located down the

road

Run campaigns on inattention

a couple of times a year

Officers have discretion to

write a caution

Tas Motorcycles, marked and

unmarked cars

Spotters at large

Hobart roundabout

Focus on fatal five, have

infringement targets for

mobile phone use

Vic Two police, one in a

position where they can

see into cars

Considering camera

detection system

Have investigated use of

metadata to prove phone in

use when offence observed

WA Motorcycle police

Plain motorcycle,

uniformed police

Two-person team with

bridge mounted

camera; one km range,

spots mobile phone

Category A offences (fatal

five) need to comprise 90%

of infringements detected

Trial of cameras and also


FINAL REPORT 35

Helmet mounted cameras

Camera footage is legal

evidence

and seat belt use

Use mapping to assist

enforcement targeting

“beacon” system – alarm

transmission when vehicle

crashes, use of phone

recorded

5.4.1 PREFERRED ENFORCEMENT PRACTICE – MOTORCYCLE POLICE

The primary challenge for enforcement is the need to observe motorists using a mobile phone

illegally. When the legislation was originally enacted, the dominant use of hand-held mobile

phones was for voice calls, which is relatively easy to detect from a car. However the

widespread current use of mobile phones for texting and social media means that they can be

held out of direct view, on the driver’s lap or by the door. Motorcycle police are positioned at

a higher eye level and able to go close to vehicles to look in, so it is not surprising that this form

of enforcement is the most popular.

In some cases, such as the NSW squads in the Sydney CBD and Parramatta, enforcement is

undertaken by sole motorcycle police, while in other cases it is undertaken by two police, one

of whom spots drivers using mobile phones and notifies the motorcycle police officer who pulls

the driver over. Because of the potential risks, sole operation is more easily undertaken when

drivers are stationary at traffic lights, while a two person operation means that the motorcycle

police officer does not need to ascertain whether the driver of a moving vehicle is using a phone

as this has already been determined by the spotter. If there was a move to place less importance

on mobile phone use while stationary (which is not seriously proposed by agencies but has

some support among the public), single officer operations would become more difficult and the

more resource-intensive two officer operation would be more appropriate, subject to technology

solutions discussed below.

5.4.2 USE OF CAMERAS

Cameras are used routinely in some jurisdictions and occasionally in others. The Australian

legal system places a high level of trust in the word of a police officer, so the need for camera

evidence of mobile phone use apart from the officer’s statement is probably unnecessary in the

majority of cases, and drivers accept the penalty. In some jurisdictions this is all that police

rely on, while in others there are varying degrees of use of cameras, which have different levels

of evidentiary standing. In WA, for example, motorcycle police have helmet cameras and the

footage taken can be used as evidence. In other jurisdictions the standing of photographic

evidence is unclear. Some motorcycle police have helmet cameras, and cameras can also be

used by police car occupants. Cameras may also be positioned on suitable vantage points, such

as overpasses, however they usually need an operator to be present to determine that an offence

has been committed, so that a police officer can pull over the vehicle.

Unlike speed camera and red light camera offences, there is no specific camera-detected mobile

phone offence with owner onus legislation to allow for automatic camera operation. The


FINAL REPORT 36

potential for more widespread use of cameras is being examined in Victoria and Western

Australia, using a system developed by the company Parking Strategy. Two uncommissioned

surveys have been undertaken by Parking Strategy in Sydney and Melbourne, where they report

(Parking Strategy, 2017):

Sydney: 418 infringements over 12 hours (about one every 103 seconds), with 4.1% of

motorists observed using a mobile phone

Melbourne on the M2 Motorway: 56 infringements were observed in 21 minutes (one

every 21 seconds)

A commissioned trial by Parking Strategy is about to be undertaken in Western Australia.

Contact was made with the company, who agreed to the citation of the figures above (from a

proposal to VicRoads). While the camera shots still need to be checked manually to confirm

mobile phone use, the company is hopeful that image processing algorithms can be developed

to allow better automatic detection. If this could be achieved, it could form the basis of an

automated enforcement approach, however it is understood that there are considerable

challenges involved in developing a successful algorithm.

5.4.3 ENFORCEMENT PRIORITY

The enforcement of mobile phone use relative to other offences is approached in different ways.

Some jurisdictions (notable WA and Tasmania) reported that, because driving while distracted

is one of the Fatal Five driver behaviours, it has a higher priority for enforcement than offences

outside the Fatal Five. In WA the Fatal Five offences are defined as Category A offences, and

90% of infringements detected need to fall into this category. In Tasmania, specific targets for

mobile phone infringements are implemented, though this may be at a regional level only.

In Sydney, the CBD motorcycle squad that undertakes a large proportion of mobile phone

enforcement was not established for this purpose, but as a means of addressing congestion in

the CBD resulting from the light rail construction being undertaken. While the nature of the

CBD traffic control task lends itself well to mobile phone enforcement, the main objective of

the squad is to facilitate traffic movement. The policy question that arises is whether such an

“incidental” focus on mobile phone enforcement is adequate.

Overall, in the larger jurisdictions, the detection of mobile phone infringements does not appear

to have kept pace with population increases, and is therefore even further behind the rate of

uptake and use of mobile phone-based applications by drivers. Several police interviewees felt

that their enforcement efforts had not made a difference to levels of use, and that the problem

needed a technological solution rather than an enforcement solution.


FINAL REPORT 37

5.5 COMMON POLICY GOALS ACROSS JURISDICTIONS

Commonality of the use of ARR 300 can be seen, though the States are not uniform in how

novice drivers are addressed and there are variations in the severity of penalties. The interviews

also identified some emerging issues and policy directions that are being considered by

jurisdictions.

5.5.1 EMERGING ISSUES AND POLICY DIRECTIONS

There is a shared view that the efforts to reduce mobile phone use while driving through

legislation and enforcement have been of limited success, and may only have slowed a tide of

increasing use. There were two main themes underlying the comments made: technological

and social.

5.5.1.1 Technological issues

In several interviews the issue of technological change was mentioned as both a challenge and

an opportunity. The introduction of greater interactivity between devices, through applications

such as Apple CarPlay, challenges the current assumptions about the functionality of mobile

phones. Since the phone is also a source of music, a potential navigation aid and collision

warning device, “using a mobile phone” covers a wider range of activities than is envisaged in

ARR 300. For P1/2 drivers in jurisdictions where all phone use is banned for these license

classes, the automatic connection of the phone for music is therefore illegal. The driver aid

features of a phone, which in theory should benefit the driver, are similarly illegal. Amending

ARR 300 to address these issues and to anticipate future technological change seems both

necessary and hard to achieve.

On the other hand, in several interviews it was stated that technology offers an answer to the

dangers of mobile phone use while driving that enforcement alone cannot address. It was less

clear what shape such an answer would take; interviewees were often aware of voluntary

blocking software and were doubtful about its value, while the impact of complete blocking

was considered to involve risks, e.g. one police interviewee remarked that the delay between a

crash in a rural area and the arrival of emergency services has been greatly reduced by the use

of mobile phones.

5.5.1.2 Social issues

Several of the interviews raised the point that, among young people in particular, the use of a

mobile phone as a form of social connection is of primary importance, while tasks like driving

are less crucial. There are different ways of expressing this, with the most extreme being

inversion of the vehicle control/mobile phone use relationship, such that the demands of driving

are seen to be a distraction from the need to maintain contact with important others. Another

perspective is to problematize mobile phone use among young people as a form of addiction.

Alternatively, a societal development perspective taken by some interviewees is that the shift


FINAL REPORT 38

to a different form of social contact though technology has happened too rapidly for society to

have developed behavioural protocols around what kinds of use are appropriate and to what

level. To address this issue, the evolution of such protocols and their inclusion in the

socialisation of children (at home and in school) is seen to be a long term means of establishing

a social framework that can be utilised to justify legislation, support compliance and legitimise

enforcement.

These perspectives have varying implications, and there is no clear direction at this stage. As

there are similar issues being experienced in other areas, for example mental health among

young people in relation to social media use, it is likely some consensus will emerge. However

this is not likely to provide guidance in the short term.

5.5.2 NATIONAL LEADERSHIP AND AN EVIDENCE-BASED APPROACH

As noted above, all jurisdictions have recourse to the Australian Road Rules, and all are

members of the Austroads Road Safety Taskforce, which has identified mobile phone use (and

distracted driving in general) as a significant policy issue. In the interviews it was noted that

ARR 300 is under review and there was a clear sense among transport agency interviewees of

a commitment to a national approach. In general, police agency interviewees considered the

policy issues to be the province of the relevant transport agency in their jurisdiction. The

interview period overlapped with an Austroads Road Safety Taskforce meeting, and contacts

interviewed after the meeting mentioned the discussions that had taken place, giving the

impression that the Taskforce provides a useful forum for exploring issues and challenges.

However, the federal structure of Australian government means that the transport agencies in

the States and Territories have more influence on transport policy than the Department of

Infrastructure and Regional Development and Austroads itself is a peak body for State and

Territory (and New Zealand) road authorities, so that national leadership in this area has to

proceed through consensus.

There is also a strong emphasis among the jurisdictions, in both transport agencies and police

agencies, on an evidence-based approach to policy on driving while distracted by mobile phones

and other devices. The lack of comprehensive and reliable crash data, and the challenge of

ever-changing technology, present challenges to an evidence-based approach. The literature

review noted that naturalistic driving studies are beginning to provide better insights into the

crash risks associated with distracted driving, and some jurisdictions have expressed interest in

exploring the implications of this research (notably Queensland and Victoria). However, the

literature review also pointed out that the interpretation of the naturalistic driving study data is

disputed, and that the dispute concerns an issue directly relevant to policy – whether it is risky

to have a mobile phone conversation on a hands-free phone. This implies that it will be difficult

to gain a clear policy direction through national consensus without first resolving the questions

surrounding the evidence. As most of this evidence is being collected and interpreted in the

United States, the ability to move forward in Australia is limited.


FINAL REPORT 39

Consideration of these points suggests that, in the short/medium term, the best way to work

towards a nationally agreed policy direction is to:

Consult researchers with relevant expertise to determine the evidence base on which

policy can be developed

Investigate means of collecting valid, reliable and comprehensive data on mobile phone

involvement in road crashes

Explore enforcement options that can be implemented by all jurisdictions

Explore technology options that balance the costs and benefits of reducing or blocking

connectivity of mobile phones in vehicles

In the longer term, the social context of mobile phone use needs to be explored and addressed,

though this would take place in a broader context and draw on social education approaches.


FINAL REPORT 40

6 SCOPE FOR EXISTING AND NEW TECHNOLOGICAL APPROACHES

6.1 EXISTING TECHNOLOGICAL APPROACHES TO REDUCING THE RISK OF MOBILE

PHONE USE

6.1.1 WORKLOAD DETECTION AND ALERTING

A basic approach to distraction is to alert drivers if they need to devote more attention to the

road. However, this approach relies on a means of measuring workload in the first place, then

developing devices that can use these measurements to trigger alerts.

6.1.1.1 Measuring workload

The main focus on workload measurement has been on cognitive workload, although visual

factors are taken into account as well. Workload can be measured at the physiological level

using an electroencephalograph (EEG), electro-oculography (EOG), eye gaze monitoring,

visual occlusion measurement, and heart rate monitoring (Mehler, Reimer & Coughlin, 2012).

Cognitive distraction may be inferred from various metrics including strong gaze concentration

to the road centre, reduction in lane-keeping variance, and/or an increase in small (usually

below 2o) steering wheel reversals.

6.1.1.2 Distraction alerts

These in-vehicle systems utilise workload measurements to warn drivers if they are judged to

be visually and/or cognitively distracted by interaction with a mobile phone or some other

source of distraction. Hence, they may reduce the risk of mobile phone use by reminding drivers

that they are distracted and helping them to re-orient their attention back to activities critical

for safe driving.

Two types exist:

Visual Distraction Alerts – warn the driver if they are judged to be glancing away from the road

for too long, or too often, and help the driver to re-focus visual attention to the roadway. Eye

glance and head-rotation metrics are commonly used to gauge the level of driver visual

distraction. Alerts may include flashing lights, icons, tones, seat vibrations and voice messages.

Cognitive Distraction Alerts – warn the driver if judged to be paying excessive attention to

internal thoughts or auditory content (e.g. day dreaming). Flashing lights on both sides of the

windscreen may be used to remind drivers to scan the road environment (particularly the

peripheries) if they are having a mobile phone conversation and gaze concentration is judged

to be too high.

The benefits of these systems are mixed. Donmez, Boyle, & Lee (2007), for example, found

that visual distraction alerts increased visual attention to the forward roadway. Others, however,


FINAL REPORT 41

have reported contradictory findings (e.g. Lee et al. 2013) or have reported that drivers perceive

alerts to be overly obtrusive and annoying (e.g. Roberts, Ghazizadeh, & Lee 2012).

Distraction alerting systems are available in some production vehicles currently on the market,

and are mainly used in fleet vehicles.

6.1.2 WORKLOAD MANAGERS IN-VEHICLE

A Workload Manager (WM) is a system that assesses continuously the difficulty of driving and

regulates the flow of information that could interfere with driving to drivers (Green, 2004).

Workload managers may thus reduce the risk of mobile phone use by reducing driver exposure

to mobile phone information and functions at times at which exposure is most likely to

compromise the performance of activities critical for safe driving. Workload managers have

been built into some production vehicles currently on the market.

The functions of WMs can be categorised into three primary groups: Information Rescheduling,

Function Lockout, and Adaptation of Information Format (Engstrom & Victor 2009).

Information Rescheduling - ensures that the driver receives information only when it is needed

and when s/he is able to receive it safely (e.g. by delaying an incoming text message until the

driver passes through an intersection).

Function Lockout - involves the entire disabling of a function or sub-function when driving is

judged to be difficult. (e.g. text messaging functionality on smartphone is disabled while driving

over a certain speed).

Adaptation of Information Format - involves changing the way information is presented, not

just its timing, based on driving demand and context (e.g. text message is read aloud to the

driver so s/he does not have to read it on a smartphone display).

WM functions, such as functional lockouts, have been found to reduce driver workload (e.g.

Wood & Hurwitz 2005) as well as reduce impairments in driving performance (Donmez, Boyle,

& Lee 2006) associated with secondary task performance.

Self-regulation support technologies - involves advising drivers of when it is safe to use their

phone through context-aware technologies. Recent research has highlighted self-regulation as

an alternative for safe mobile phone use while driving (Oviedo-Trespalacios et al., 2016;

Oviedo-Trespalacios et al., 2017a; Oviedo-Trespalacios et al., 2017b).

Gamification – The term gamification refers to the use of game design, game playing techniques

and game mechanisms to engage users and motivate positive behaviour. Gamified systems can

be embedded in mobile phone devices to support driving functions while avoiding distraction

(Vaezipour, 2015; Vaezipour et al, 2015; Orfilia et al., 2016; Vaezipour et al, 2016; Vaezipour

et al, 2017). Distraction can be prevented using ambient devices feedback and altruistic

motivations.


FINAL REPORT 42

6.1.3 WORKLOAD MANAGERS: APPLICATIONS ON MOBILE PHONES

Some Workload Manager-like applications have also been developed for mobile phones:

AT&T Drive Mode (Information Rescheduling) – this app silences all phone

notifications when travelling over 25 km/hr. The app is self-enabled

(http://www.att.com/gen/press-room?pid=23185)

Cellcontrol (Function Lockout) – is a device installed under the dashboard that

communicates with an app on the phone which prevents children from gaining

access to text messaging, email and camera functionality while driving. This

application cannot be disabled by the child. The device is designed for parents

(https://www.cellcontrol.com/)

Live2Txt (Function lockout) - a self-enabled app that blocks the phone from

receiving texts and calls (http://www.getlive2txt.com/)

Drivemode (Adaptation of Information Format) – a self-enabled app that

allows text messages, received while driving, to be read aloud by a voice on

the phone with the aim of keeping the driver’s eyes on road

(https://drivemode.com/).

Drivesafe.ly (Adaptation of Information Format) - Similar to Drivemode.

Reads text messages and emails aloud while driving. This app is self-enabled.

(http://www.drivesafe.ly/)

No data on the effectiveness nor the acceptance of these systems is known to the authors,

although (as noted in section 6.4) there is some recent research from a fleet experiment in South

Australia that indicates a problem with acceptance.

6.2 NEW AND POTENTIALLY EMERGING TECHNOLOGIES THAT HAVE PROMISE

6.2.1 TECHNOLOGIES TO SUPPORT POLICE ENFORCEMENT OF DISTRACTION LAWS

ComSonics, based in Virginia, USA, has developed a radar gun-type device, which is capable

monitoring, scanning, and identifying radio signals associated with cellphone use. It is

reportedly capable of detecting unique radio frequencies emitted by cellphones when text

messages are sent (Forster, 2014). It is not known if the device has yet been deployed in the

US, or elsewhere. As at 2014, the device was reportedly close to production

(https://www.digitaltrends.com/cars/step-away-iphone-virginia-company-developing-radar-

gun-help-catch-texting-drivers/).

Norfolk County Council in the UK and the firm Westotec have trialled a device that detects

whether a mobile phone is being used in a moving car. Mobile Phone Detection System (MPDS)

is a portable technology that is able to tell if a mobile phone is being used in a moving vehicle,

regardless of whether they are conversing or receiving/sending a text message. A roadside

http://www.att.com/gen/press-room?pid=23185

https://www.cellcontrol.com/

http://www.getlive2txt.com/

https://drivemode.com/

https://www.digitaltrends.com/cars/step-away-iphone-virginia-company-developing-radar-gun-help-catch-texting-drivers/

https://www.digitaltrends.com/cars/step-away-iphone-virginia-company-developing-radar-gun-help-catch-texting-drivers/


FINAL REPORT 43

sensor monitors oncoming vehicles and sends information to a sign upstream which flashes

when mobile phone use has been detected in the vehicle. The technology was not aimed

originally at issuing infringements for illegal mobile phone use; but, rather, to remind drivers

of distraction laws (Rayner, 2015). However, the technology has since been modified to turn it

into a speed-camera style automatic fine collector. If a mobile phone is detected in a moving

vehicle, a photo is taken which is then used to determine if the driver was the person on board

using the phone (http://road.cc/content/news/142406-speed-camera-style-mobile-phone-

detectors-could-spot-drivers-talking-wheel-and).

We are not aware of any published studies that have evaluated the effectiveness of these

technologies.

6.2.2 TECHNOLOGIES THAT AIM TO KEEP DRIVERS’ EYES ON THE ROAD

Windscreen Head-Up Displays (HUDs) project information onto the vehicle windscreen in line

with the driver’s forward line of sight. Windscreen HUDs are associated with a number of

driving performance benefits compared with conventional, or head-down, displays (Briziarelli

& Allen, 1989; Sojourner & Antin, 1990; Horrey, Wickens & Alexander, 2003; Liu, 2003; Liu

& Wen, 2004; Ablaßmeier et al., 2007. Generally, they yield fewer decrements in driving

performance and shorter gazes away from the forward roadway.

The benefits of windscreen HUDS may be diminished, however, if too much information is

presented on the HUD.

6.3 EVOLVING TECHNOLOGIES THAT CAN CONTRIBUTE TO DRIVER DISTRACTION

6.3.1 SMARTWATCHES

Smartwatches can be used to perform many of the same functions as a smartphone. The screen

through which a driver interacts with the device is, however, much smaller than that of a

smartphone, which may be more visually distracting.

One study demonstrates this. Giang, Shanti, Chen, Zhou, & Donmez (2015) find that drivers

are more likely to glance at notifications on a smartwatch than on a smartphone and that they

displayed more impaired brake response times when using a smartwatch than when using a

smartphone.

6.3.2 HEAD-MOUNTED DISPLAYS

Head-mounted displays project information in the driver’s forward field of view onto a

wearable display (e.g. Google Glass)

Google Glass comprises a small, monocular, transparent display mounted on a framework like

a standard pair of glasses (Young et al. 2016). Google Glass has been investigated in five known

http://road.cc/content/news/142406-speed-camera-style-mobile-phone-detectors-could-spot-drivers-talking-wheel-and

http://road.cc/content/news/142406-speed-camera-style-mobile-phone-detectors-could-spot-drivers-talking-wheel-and


FINAL REPORT 44

studies. Of these, four focus on the impact of voice-texting on driving performance (Sawyer et

al.,2014; Tippey et al., 2014; He et al., 2015; Young et al., 2016); the remaining one looks at

use of Google Glass for entering destination input by voice into a navigation system (Beckers

et al., 2014).

Generally, it is found that, compared to manual texting, voice texting using Google Glass results

in better lane keeping performance. However, compared to baseline driving (without Google

Glass), voice texting using Google Glass results in more missed event detections, increased

reaction time to road events (e.g. lead car braking), and more variable lane keeping.

6.3.3 FITNESS-TRACKING DEVICES

Wearable fitness-tracking devices are used to monitor an individual’s physical activity (e.g.

heart rate, steps taken). Generally they are worn on the wrist, like a conventional watch. Some

devices, such as Fitbit Surge, can be wirelessly connected to a smartphone and notify the user

when a call or text message has been received on the smartphone through a vibration transmitted

through the device. Visual information relating to the call/text, such as the caller’s name, or

even a text message, can be displayed on the device.

We are not currently aware of any published material that has assessed the distraction potential

of this technology.

6.4 RECOMMENDED TECHNOLOGICAL APPROACHES

It is clear from the comments above on new and existing technological approaches that there is

a lack of research data on which to base best practice. This is not confined to distraction by

mobile phones, but applies to the issue of distracted driving more generally. In an effort to

address this shortcoming, an EU project consulted with experts to develop consensus on “good

practice” approaches to distracted driving (TRL, TNO & Rapp Trans, 2015). Although the

report was published two years ago, it remains relevant because the study adopted a highly

structured approach based on the characteristics of approaches to distraction rather than

focusing on particular products. The assessment of good practice was applied not only to

technological approaches to distraction, but also to public education, driver licensing and

research. The technology-based approaches covered workload managers and phone blocking

systems, in addition to warning systems for collisions and drowsiness, and regulatory

approaches such as certification of apps and devices and HMI guidelines to ensure product

standardisation. These approaches were assessed in terms of their impact on distracted driving,

their costs and benefits, and the barriers to, opportunities for, their deployment.

Overall, of all approaches to distracted driving (both technological and non-technological),

workload managers considered to be the least effective approach, followed by certification and

then by phone blocking technology. The most effective approach was a technological one –

collision warning systems. In the context of mobile phone distracted driving this is an


FINAL REPORT 45

intervention which does not prevent distraction, but alerts drivers who may be distracted of an

imminent collision (or risk thereof, such as through lane deviation). Looking at the scores

assigned by the experts consulted, the low rating of workload managers and phone blockers

was primarily due to their assessment as having low user acceptance. Workload managers and

phone blockers were also considered relatively less easy to deploy, although phone blockers

were considered to be as cost-effective as collision warning systems.

It is worth noting that workload managers and phone blockers were not rated as highly on

maturity of technology as collision warning devices; as two years have elapsed since the report,

more recent research was sought, and a South Australian study focused on fleet vehicles was

identified (Ponte, Baldock & Thompson, 2016). In a fleet setting it would be reasonable to

expect a greater chance of success and acceptance of phone blocking, however the researchers

found that the participants had more negative attitudes to phone blocking after the trial than

before it, as a result of problems with the two technologies trialled: one involving software on

the phone, and the other having both phone software and pairing the phone with external

Bluetooth hardware. The problems experienced included: blocking did not work; blocking

occurred when it should not have (after journey or on weekends); difficulty overriding the

blocking when necessary; and blocking of passengers phones. These experiences suggest that

phone blocking technology still requires further development.

An alternative approach to phone blocking is to encourage voluntary use of the various apps

that are appearing, provided by manufacturers (e.g. Android, Apple), developed privately (e.g.

LifeSaver, DriveSafe Mode) and either provided or supported by telecommunications

companies (e.g. Telstra’s Drive Mode, Vodafone’s provision of links to blocking programs).

Often these apps are aimed at parents to impose in a non-voluntary way on their teen children

as drivers, however a recent review found that teenagers try to bypass such restrictions and

recommends embedding blocking technologies into broader behavioural approaches, such as

incentives provided by parents or insurers (Delgado, Wanner & McDonald, 2016).

Taken together, the findings outlined above suggest that: phone blocking technology requires

further development to improve its performance and win user acceptance; workload managers

may have promise in the future, but are at a less advanced stage of development than phone

blocking technology; and that collision warning devices have the greatest potential, even though

address distraction as it occurs rather than preventing it.


FINAL REPORT 46

7 NOMADIC DEVICES AND IN-CAR SYSTEMS

Pervasive computing and nomadic devices are becoming more common as part of digital

environments that sense, adapt, and respond to human needs. The advances in such connected

devices as part of the development of the Internet of Things (IoT) are increasingly being seen

in cars, either integrated into the vehicle operating system or as a standalone system. Nomadic

devices such as smartphones have not been designed with car use and safety in mind. Multiple

new devices may compete for a driver’s attention and therefore pose driver distraction problems

while driving. To avoid this, the integration of nomadic devices in vehicles would ideally

present a distraction-free interface, and consider safety, functionality and usability.

Figure 7.1 Cars have become highly complex with many interconnected systems

Source: CBInsights, www.cbinsights.com.

7.1 APPLE CARPLAY AND ANDROID AUTO

Apple CarPlay and Android Auto allow a smartphone (iPhone or Android phone, respectively)

to be connected to the vehicle, such that some of its features can be hosted by the human-

machine interface (HMI). These systems usually work through an on-board touch screen in the

vehicle (usually the vehicle navigation system) and support navigation, phone calls, and

messaging.

Displays in the vehicle are not always necessary. Apple's Siri Eyes Free, for example, enables

drivers to use many Apple CarPlay features through voice commands without the need for an

in-vehicle touch screen.

http://www.cbinsights.com/


FINAL REPORT 47

Many new connected vehicles include support for both Apple CarPlay and Android Auto, and

older cars can be upgraded to use them with aftermarket double-DIN entertainment consoles

(e.g. Pioneer AVH-4100NEX).

We are not aware of any published material that has evaluated specifically Apple CarPlay and

Android Auto software. However, there is preliminary research on integrated hands-free mobile

phone functionality (e.g. conversing and composing text messages) which can be hosted by

these products. This is discussed below.

7.2 INTEGRATED HANDS-FREE MOBILE PHONE CONVERSATIONS

Integrated hands-free mobile phone (IHF) conversation involves wireless connectivity between

the vehicle’s built-in hardware and the mobile phone, typically through Bluetooth; that is, short-

range radio waves that have a maximum reach of approximately 10m. Essentially, this

connectivity serves two primary functions:

Allows phone functionality and content to be accessed through the vehicle hardware

itself (e.g. accessing/reading mobile phone text messages on the IVIS screen)

Allows the driver to use the mobile phone hands-free (i.e. compose a text message

using voice activation, in which the car /microphone speakers process the spoken

words, compose a text message, and relay this message back to the mobile phone to

send).

Six known studies have examined the link between integrated hands-free mobile phone (IHF)

conversations and driving performance and safety risk.

Overall, the results of the studies reveal that driver interactions with IHF, for example to initiate

a conversation or end a call using voice input, tend to be associated with fewer decrements in

driving performance compared with visual-manual mobile phone interactions. Specifically,

drivers tend to look away from the roadway less often, and for less time (e.g. Mehler et al.

2016), and have faster reaction times to road events (Maciej & Vollrath 2009) with IHF (and

voice input) compared to visual-manual mobile phone interactions.

However, IHF often does not completely eliminate the need to manually operate a mobile phone

or the IVIS to undertake a phone-related task. Many integrated or fixed systems still allow, and

sometimes require, visual-manual interactions. For example, Fitch et al. (2013) found that, even

though the IHF conversations themselves didn’t take eyes off the road any more than baseline

driving, behaviours such as beginning/answering the call, as well as ending it, increased eyes-

off-road time by around 40%.

Two NDSs examined the link between IHF conversations and safety (Young & Schreiner 2009;

Fitch et al. 2015). Both studies suggest that IHF conversations actually reduce the risk of having

a safety critical event compared to baseline driving (i.e. driving while not engaged in an IHF

conversation). The reasons for these findings are not properly understood by the research

community.

https://www.amazon.com/Pioneer-AVH-4100NEX-Multimedia-Receiver-Touchscreen/dp/B00SKJPKGW?SubscriptionId=AKIAICE7LOAJMK3SSLPA&tag=pcm_bin-20&linkCode=xm2&camp=2025&creative=165953&creativeASIN=B00SKJPKGW

https://www.amazon.com/Pioneer-AVH-4100NEX-Multimedia-Receiver-Touchscreen/dp/B00SKJPKGW?SubscriptionId=AKIAICE7LOAJMK3SSLPA&tag=pcm_bin-20&linkCode=xm2&camp=2025&creative=165953&creativeASIN=B00SKJPKGW


FINAL REPORT 48

7.3 TEXT MESSAGING USING IVS

Two studies have explored the impact of IHF mobile phone text messaging on driving

performance. During such interactions, the driver typically voices a message which is then

processed by the vehicle microphone/speakers and converted to text (i.e. speech-to-text

technology). This message is wirelessly relayed to the mobile phone as a text message ready to

be sent (or is sent).

Compared to manual, or conventional, text messaging, using IHF is associated with fewer

driving decrements such as less and shorter glances away from the roadway, reduced steering

wheel position variance and less rapid steering corrections (Owens, McLaughlin, & Sudweeks,

2011).

However, when compared to baseline driving, IHF interactions are associated with poorer

driving performance, delayed reaction time to critical road events and a greater number (and

length) of glances away from the roadway (Owens, McLaughlin, & Sudweeks 2011; Coleman

et al. 2016).

Thus, even though the biomechanical requirements of composing a text message are reduced

with the use of IHF, the cognitive component of this interaction remains (e.g. thinking about

what to communicate, how to communicate it etc.). This cognitive demand may, in turn, impact

on the ability of the driver to detect hazards in the forward roadway (e.g. Strayer, Drews &

Johnston 2003), and in the periphery due to visual tunnelling effects (Recarte & Nunes 2003).

This may account for the performance decrements associated with voice interactions when

compared with baseline driving.


FINAL REPORT 49

8 DISCUSSION

The problem of mobile phone distraction while driving is one of many manifestations of digital

disruption, where technological change is challenging social arrangements and the ability of

governments to regulate public activities. In the area of driving, one of the major ways that this

digital disruption is expressed is by a recasting of the driving task as a distraction from the

social need to remain in contact via social media and phone conversations, whereas the

customary approach has been to view driving as the preeminent task and phone use as the

distraction. This recasting of the driving/communicating relationship (among young people in

particular) has taken place in the context of a dramatic increase in the range and uptake of

communication technologies and applications.

Until recently, the main form of evidence for the crash risk associated with mobile phone use

came from laboratory or simulator studies, and occasional hospital-based studies that used

forms of case-control methodology. Crash data has always been lacking because of the

difficulties involved in determining whether a phone was being used at the time of the

crash. This was evident in the data accessed for this project, where there were very few crashes

where mobile phone use was identified as a contributing factor. However, recent reports from

naturalistic driving studies, mostly in the United States, are beginning to address this gap. In

general, data from naturalistic studies shows a high prevalence of driving while distracted, and

significant increases in crash risk when a mobile phone is being used in hand-held mode, while

texting, reading emails and browsing. Unfortunately it is not clear whether conversation alone

increases crash risk because there is a debate about the validity of the methods used to calculate

the odds ratios that have been generated from the naturalistic data. This is an area where future

research is needed, as the risk associated with conversing is relevant to the consideration of

appropriate regulations on mobile phone use.

In addition to seeking some kind of resolution of the debate over the naturalistic crash data, it

would be worth addressing the collection of crash data in some way. For example, there has

been previous discussion of the mandatory installation of a microchip known as a “controlled

area network (CAN) bus” that would have a buffer that contains the record of vehicle operation

information immediately before an event such as a crash. Under the Australian Design Rules,

new buses and trucks are required to have a CAN bus fitted for other data logging purposes,

and it is understood that most new cars are fitted with them. There are already CAN bus

products on the market that have Wi-Fi and Bluetooth capability. If the CAN bus was able to

record mobile phone use (including an identifying code to ascertain which phone it was) this

would provide both better data and assistance to police in identifying the contribution of

distraction to the crash. In the short term it would also be worthwhile further exploring the data

available in the National Coronial Information System, perhaps through a text mining approach,

i.e. an algorithm to automatically read the text information in coronial records and extract

information on mobile phone use. While fatalities are relatively small in number, the

circumstances of the crashes are better researched and documented than non-fatal crashes.


FINAL REPORT 50

Regulatory frameworks in Australia are based on ARR 300, but there are variations by

jurisdiction that are worth examining further, in terms of consistency of approach (defined

offences, penalty levels) and justification (related to the range of risk levels identified for

different forms of distraction by mobile phones in naturalistic studies). As there is an overlap

between policy approaches, for example the mobile phone restrictions imposed in Graduated

Driver Licensing schemes, this would involve consultation with a broader range of

stakeholders.

The police and some transport agencies have doubts about the effectiveness of enforcement as

a way of reducing mobile phone use. While automated enforcement using cameras would

address this problem, this requires the development of an image processing algorithm that can

successfully identify mobile phone use by drivers, which is considered (at the least) a difficult

task. Further research development of such an algorithm would be of benefit in determining

the value of this approach. The possibility of self-enforcement through apps may be worth

following up, though interviewees were not optimistic about the chances of

success. Technological enforcement approaches involving blocking have negative

implications, however there are emerging technologies that may be able to measure workload

and control the driver’s access to communication in accordance with workload, although as

noted in section 6 these technologies still lack maturity and public acceptance.

From a government and policy perspective, the need for a national consensus among

jurisdictions and an evidence-based approach to policy should shape the approach taken. In the

short/medium term, taking into account the points raised above, this would involve:

Consulting researchers with relevant expertise to determine the evidence base on

which policy can be developed, including a resolution of the debate on the validity of

naturalistic driving study crash risk estimates

Investigating means of collecting valid, reliable and comprehensive data on mobile

phone involvement in road crashes, such as wifi and Bluetooth-enabled CNN bus

microchips that record mobile phone use in the vehicle

Exploring enforcement options that can be implemented by all jurisdictions, including

the possibility of automated enforcement by cameras, provided a successful detection

algorithm can be developed within a reasonable timeframe

Exploring technology options that balance the costs and benefits of reducing or

blocking connectivity of mobile phones in vehicles

In addition, the broader effects of digital disruption on society, and especially the social

functioning of young people, have relevance to the use of mobile phones while driving. In the

longer term, the social context of mobile phone use needs to be explored and addressed, with

the aim of establishing a social framework that enables young people to interact with social

media in less harmful ways. Such a framework could be utilised to justify legislation, support

compliance and legitimise enforcement.


FINAL REPORT 51

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FINAL REPORT 72

APPENDIX A INTERVIEW SCHEDULE

LEGISLATION AND ENFORCEMENT

My understanding of your current regulations is that (read summary of information collected on

this):

Is this a reasonable summary?

Is this an adequate system (prompt for problematic cases that have occurred)

Are there changes planned or regulation issues that are under discussion?

I would also like to talk about the way the legislation is enforced; from information we have

collected so far, we understand that your current practices are (read summary of information

collected on this):

Is this a reasonably accurate description?

What kinds of difficulty have been experienced and how have they been addressed?

Are you considering other options for enforcement?

CRASH DATA

Are sources of distraction and inattention, and specifically the use of mobile phones and devices

routinely considered as potential contributing factors of a crash?

What threshold of evidence is needed to determine that mobile phone/device use contributed to

the crash as opposed to whether it was (strongly) suspected?

What barriers have police officers experienced in determining whether mobile phone/device use

was a contributory factor of the crash?

Do the notes and detailed reports of investigations record that mobile phone/device use was

considered but could not be confirmed at the required evidentiary threshold?

If the detailed reports of the crash investigation record that mobile phone/device use was

confirmed as a contributing factor are there limitations in the crash databases that may result in

under reporting its role? (prompt for possibilities)


FINAL REPORT 73

APPENDIX B SUMMARY OF DRIVER DISTRACTION LAWS ACROSS DIFFERENT JURISDICTIONS (ADAPTED FROM WHO REPORT, 2011)

Table B.1 Driver distraction laws in New Zealand

While driving a vehicle, a driver must not – (a) use a mobile phone to make, receive, or terminate a telephone call; or (b) use a mobile phone to create, send, or read a text message; or (c) use a mobile phone to create, send, or read an email; or (d) use a mobile phone to create, send, or view a video message; or (e) use a mobile phone to communicate in a way similar to a way described in any of paragraphs (b) to (d); or (f) use a mobile phone in a way other than a way described in any of paragraphs (a) to (e). (1A) Subclause (1) is overridden by subclauses (2) to (7). (2) An enforcement officer may, while driving a vehicle, use a mobile phone to make, receive, or terminate a telephone call if the officer is making, receiving, or terminating the call in the execution of the officer's duty. (3) A driver may, while driving a vehicle, use a mobile phone if— (a) the driver is using the phone to make a 111 or *555 call; and (b) it is unsafe or impracticable for the driver to stop and park the vehicle to make the call. (4) A driver may, while driving a vehicle, use a mobile phone to make, receive, or terminate a telephone call if the phone does not require the driver to hold or manipulate it to make, receive, or terminate the call. (5) [Revoked] (6) A driver may, while driving a vehicle, use a mobile phone to make, receive, or terminate a telephone call if the vehicle has stopped for a reason other than the normal starting and stopping of vehicles in a flow of traffic. (7) A driver may, while driving a vehicle, use a mobile phone in a way described in subclause (1)(a) or (f), if both the following apply: (a) the phone is secured in a mounting fixed to the vehicle; and (b) if the driver manipulates or looks at the phone, he or she does so infrequently and briefly.

A mobile phone is defined as — (a) includes a portable electronic device whose functions include being a telephone: (b) does not include a CB radio: (c) does not include any other kind of two-way radio:

(d) does not include an earpiece or mouthpiece that is connected, physically or otherwise, to a mobile phone to allow a driver to use the

phone without holding or manipulating it

Visual display units 2.5(1) Except as provided in 2.5(2), any part of the image on a television screen fitted in a motor vehicle must not be visible to the driver of the motor vehicle from his or her normal driving position while the motor vehicle is in motion. 2.5(2) Subclause 2.5(1) does not apply if:

(a) the television screen is fitted in the motor vehicle only for the purpose of assisting the driver to reverse safely, by showing a clear picture of the area directly behind the motor vehicle; or

(b) the motor vehicle is a passenger service vehicle and the provisions of Land Transport Rule: Passenger Service Vehicles 1999 are complied with; or

(c) the screen is fitted as original equipment by the vehicle manufacturer and is designed so that only information relating to the navigation, safe operation and control of the motor vehicle can be displayed on the screen while the motor vehicle is in motion; or

(d) the screen is only capable of displaying text and any change to the text on the screen is controlled manually by the driver.

https://www.nzta.govt.nz/resources/rules/vehicle-equipment-2004/#252

https://www.nzta.govt.nz/resources/rules/vehicle-equipment-2004/#251

https://www.nzta.govt.nz/resources/rules/passenger-service-vehicles-1999/

https://www.nzta.govt.nz/resources/rules/passenger-service-vehicles-1999/


FINAL REPORT 74

Table B.2 Driver distraction laws UK – mobile phones

(1) No person shall drive a motor vehicle on a road if he is using— (a) a hand-held mobile telephone; or (b) a hand-held device of a kind specified in paragraph (4).

(2) No person shall cause or permit any other person to drive a motor vehicle on a road while that other person is using— (a) a hand-held mobile telephone; or (b) a hand-held device of a kind specified in paragraph (4).

(3) No person shall supervise a holder of a provisional license if the person supervising is using— (a) a hand-held mobile telephone; or (b) a hand-held device of a kind specified in paragraph (4), at a time when the provisional license holder is driving a motor vehicle on a road.

(4) A device referred to in paragraphs (1)(b), (2)(b) and (3)(b) is a device, other than a two-way radio, which performs an interactive communication function by transmitting and receiving data. (5) A person does not contravene a provision of this regulation if, at the time of the alleged contravention—

(a )he is using the telephone or other device to call the police, fire, ambulance or other emergency service on 112 or 999; (b) he is acting in response to a genuine emergency; and (c) it is unsafe or impracticable for him to cease driving in order to make the call (or, in the case of an alleged contravention of paragraph (3)(b), for the provisional licence holder to cease driving while the call was being made).

(6) For the purposes of this regulation— (a) a mobile telephone or other device is to be treated as hand-held if it is, or must be, held at some point during the course of making or receiving a call or performing any other interactive communication function; (b) a person supervises the holder of a provisional licence if he does so pursuant to a condition imposed on that licence holder prescribed under section 97(3)(a) of the Road Traffic Act 1988 (grant of provisional licence); (c)“interactive communication function” includes the following:

(i)sending or receiving oral or written messages; (ii)sending or receiving facsimile documents; (iii)sending or receiving still or moving images; and (iv)providing access to the internet;

(d) “two-way radio” means any wireless telegraphy apparatus which is designed or adapted— (i) for the purpose of transmitting and receiving spoken messages; and (ii) to operate on any frequency other than 880 MHz to 915 MHz, 925 MHz to 960 MHz, 1710 MHz to 1785 MHz, 1805 MHz to 1880 MHz, 1900 MHz to 1980 MHz or 2110 MHz to 2170 MHz; and (a) “wireless telegraphy” has the same meaning as in section 19(1) of the Wireless Telegraphy Act 1949(2).”

Table B.3 Driver distraction laws UK – visual display units

(1) No person shall driver, or cause or permit to be driven, a motor vehicle on a road, if the driver is in such a position as to be able to

see, whether directly or by reflection, a television receiving apparatus or other cinematographic apparatus used to display

anything other than information –

(a) About the state of the vehicle or its equipment;

(b) About the location of the vehicle and the road on which it is located;

(c) To assist the driver see the road adjacent to the vehicle; or

(d) To assist the driver to reach his destination.

(2) In this regulation “television receiving apparatus” means any cathode ray tube carried on a vehicle and on which there can be

displayed an image derived from a television broadcast, a recording or a camera or computer.

http://www.legislation.gov.uk/uksi/2003/2695/regulation/2/made#f00003


FINAL REPORT 75

Table B.4 Driver distraction laws U.S.

State Hand-held cell

phone ban

All cell phone ban Text messaging

ban

Video screen restriction (Yes/No)

School bus drivers Novice drivers

Alabama None None 16 or 17 w/ license

<6 months

All drivers Y

Alaska None None None All drivers Y

Arizona None Yes None None Y

Arkansas Only drivers 18-20

years old

Yes <18 All drivers N

California Yes Yes <18 All drivers Y

Colorado None <18 All drivers N

Connecticut Yes Yes <18 All drivers Y

Delaware Yes Yes Learner or

intermediate license

holders only

All drivers N

D.C. Yes Yes Learners permit only All drivers Y

Florida None None None All drivers Y

Georgia None Yes <18 All drivers N

Hawaii Yes None <18 All drivers N

Idaho None None None All drivers N

Illinois Yes Yes <19 All drivers N

Indiana None None <21 (effective 7/15) All drivers Y

Iowa None None Restricted or


holder only

All drivers N

Kansas None None Learner or


holders only

All drivers N

Kentucky None Yes <18 All drivers N

Louisiana Learner or


holders only

Yes 1st year of license or

<18

All drivers Y

Maine None None Learner or


holders only

All drivers Y

Maryland Yes None <18 All drivers Y

Massachusetts None Yes <18 All drivers Y

Michigan None Yes Level 1 or 2 license

holder only

All drivers Y

Minnesota None Yes <18 w/ learner or

provisional license

All drivers Y

Mississippi None Yes None All drivers N

Missouri None None None Only drivers 21

years of age or less

N

Montana None None None None N


FINAL REPORT 76

State Hand-held cell

phone ban

All cell phone ban Text messaging

ban

Video screen restriction (Yes/No)

School bus drivers Novice drivers

Nebraska None None <18 w/ learner or


All drivers Y

Nevada Yes None None All drivers Y

New Hampshire Yes None <18 All drivers Y

New Jersey Yes Yes Permit or provisional

license only

All drivers Y

New Mexico In state vehicles

only

None Learner or

provisional license

only

All drivers Y

New York Yes None None All drivers Y

North Carolina None Yes <18 All drivers Y

North Dakota None None <18 All drivers N

Ohio None None <18 All drivers N

Oklahoma Learner or


holders only

None None All drivers (effective

11/15)

Y

Oregon Yes None <18 All drivers Y

Pennsylvania None None None All drivers Y

Rhode Island None Yes <18 All drivers Y

South Carolina None None None All drivers Y

South Dakota None None Learner or


holders only

All drivers Y

Tennessee None Yes Learner or


holders only

All drivers Y

Texas None Yes when w/

passenger 17 years

or younger

<18 Only when (a) w/ a

passenger 17 or

younger, and (b)

driver is younger

than 18 years

Y

Utah None Yes <18 All drivers Y

Vermont Yes None <18 All drivers Y

Virginia None Yes <18 All drivers Y

Washington Yes None Learner or


holders only

All drivers Y

West Virginia Yes None <18 w/ learner or


All drivers Y

Wisconsin None None Learner or


holders only

All drivers Y

Wyoming None None None All drivers Y

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